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  <doc>
    <id>3342</id>
    <completedYear>2025</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>11</issue>
    <volume>15</volume>
    <type>article</type>
    <publisherName>MDPI</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2025-05-30</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Advancing Image Spam Detection: Evaluating Machine Learning Models Through Comparative Analysis</title>
    <abstract language="eng">Image-based spam poses a significant challenge for traditional text-based filters, as malicious content is often embedded within images to bypass keyword detection techniques. This study investigates and compares the performance of six machine learning models—ResNet50, XGBoost, Logistic Regression, LightGBM, Support Vector Machine (SVM), and VGG16—using a curated dataset containing 678 legitimate (ham) and 520 spam images. The novelty of this research lies in its comprehensive side-by-side evaluation of diverse models on the same dataset, using standardized dataset preprocessing, balanced data splits, and validation techniques. Model performance was assessed using evaluation metrics such as accuracy, receiver operating characteristic (ROC) curve, precision, recall, and area under the curve (AUC). The results indicate that ResNet50 achieved the highest classification performance, followed closely by XGBoost and Logistic Regression. This work provides practical insights into the strengths and limitations of traditional, ensemble-based, and deep learning models for image-based spam detection. The findings can support the development of more effective and generalizable spam filtering solutions in multimedia-rich communication platforms.</abstract>
    <parentTitle language="eng">Applied Sciences</parentTitle>
    <identifier type="issn">2076-3417</identifier>
    <identifier type="doi">10.3390/app15116158</identifier>
    <enrichment key="opus.import.date">2025-06-09T13:45:16+00:00</enrichment>
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    <enrichment key="PeerReviewNachweis">ja</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Mahnoor Jamil</author>
    <author>Hristina Mihajloska Trpcheska</author>
    <author>Aleksandra Popovska-Mitrovikj</author>
    <author>Vesna Dimitrova</author>
    <author>Reiner Creutzburg</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>spam detection</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>image spam</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>machine learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Support Vector Machine</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>XGBoost</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Logistic Regression</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>ResNet50</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>LightGBM</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>VGG16</value>
    </subject>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <collection role="Import" number="import">Import</collection>
  </doc>
  <doc>
    <id>3317</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>355-1</pageFirst>
    <pageLast>355-15</pageLast>
    <pageNumber/>
    <edition/>
    <issue>3</issue>
    <volume>35</volume>
    <type>article</type>
    <publisherName>Society for Imaging Science and Technology (IS&amp;T)</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2025-04-10</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Practical OSINT investigation in Twitter utilizing AI-based aggressiveness analysis</title>
    <abstract language="eng">Open-source intelligence is gaining popularity due to the rapid development of social networks. There is more and more information in the public domain. One of the most popular social networks is Twitter. It was chosen to analyze the dependence of changes in the number of likes, reposts, quotes and retweets on the aggressiveness of the post text for a separate profile, as this information can be important not only for the owner of the channel in the social network, but also for other studies that in some way influence user accounts and their behavior in the social network. Furthermore, this work includes a detailed analysis and evaluation of the Tweety library capabilities and situations in which it can be effectively applied. Lastly, this work includes the creation and description of a compiled neural network whose purpose is to predict changes in the number of likes, reposts, quotes, and retweets from the aggressiveness of the post text for a separate profile.</abstract>
    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="doi">10.2352/EI.2023.35.3.MOBMU-355</identifier>
    <enrichment key="PeerReviewNachweis">ja</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Keine Nutzungslizenz vergeben - es gilt das deutsche Urheberrecht</licence>
    <author>Artem Skylar</author>
    <author>Klaus Schwarz</author>
    <author>Reiner Creutzburg</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>3316</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>356-1</pageFirst>
    <pageLast>356-10</pageLast>
    <pageNumber>10</pageNumber>
    <edition/>
    <issue>3</issue>
    <volume>35</volume>
    <type>article</type>
    <publisherName>Society for Imaging Science and Technology (IS&amp;T)</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2025-04-10</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Practical OSINT investigation - Similarity calculation using Reddit user profile data</title>
    <abstract language="eng">This paper presents a practical Open Source Intelligence (OSINT) use case for user similarity measurements with the use of open profile data from the Reddit social network. This PoC work combines the open data from Reddit and the part of the state-of-the-art BERT model. Using the PRAW Python library, the project fetches comments and posts of users. Then these texts are converted into a feature vector - representation of all user posts and comments. The main idea here is to create a comparable user's pair similarity score based on their comments and posts. For example, if we fix one user and calculate scores of all mutual pairs with other users, we will produce a total order on the set of all mutual pairs with that user. This total order can be described as a degree of written similarity with this chosen user. A set of "similar" users for one particular user can be used to recommend to the user interesting for him people. The similarity score also has a "transitive property": if $user_1$ is "similar" to $user_2$ and $user_2$ is similar to $user_3$ then inner properties of our model guarantees that $user_1$ and $user_3$ are pretty "similar" too. In this way, this score can be used to cluster a set of users into sets of "similar" users. It could be used in some recommendation algorithms or tune already existing algorithms to consider a cluster's peculiarities. Also, we can extend our model and calculate feature vectors for subreddits. In that way, we can find similar to the user's subreddits and recommend them to him.</abstract>
    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="doi">10.2352/EI.2023.35.3.MOBMU-356</identifier>
    <enrichment key="PeerReviewNachweis">ja</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
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    <licence>Keine Nutzungslizenz vergeben - es gilt das deutsche Urheberrecht</licence>
    <author>Valeria Vishnevskaya</author>
    <author>Klaus Schwarz</author>
    <author>Reiner Creutzburg</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>3314</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>357-1</pageFirst>
    <pageLast>357-12</pageLast>
    <pageNumber/>
    <edition/>
    <issue>3</issue>
    <volume>35</volume>
    <type>article</type>
    <publisherName>Society for Imaging Science and Technology (IS&amp;T)</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2025-04-10</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Open-source Intelligence (OSINT) investigation in Facebook</title>
    <abstract language="eng">Open Source Intelligence (OSINT) has come a long way, and it is still developing ideas, and lots of investigations are yet to happen in the near future. The main essential requirement for all the OSINT investigations is the information that is valuable data from a good source. This paper discusses various tools and methodologies related to Facebook data collection and analyzes part of the collected data. At the end of the paper, the reader will get a deep and clear insight into the available techniques, tools, and descriptions about tools that are present to scrape the data out of the Facebook platform and the types of investigations and analyses that the gathered data can do.</abstract>
    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="doi">10.2352/EI.2023.35.3.MOBMU-357</identifier>
    <enrichment key="PeerReviewNachweis">ja</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Keine Nutzungslizenz vergeben - es gilt das deutsche Urheberrecht</licence>
    <author>Pranesh Kumar Narasimhan</author>
    <author>Chinmay Bhosale</author>
    <author>Muhammad Hasban Pervez</author>
    <author>Najiba Zainab Naqvi</author>
    <author>Mert Ilhan Ecevit</author>
    <author>Klaus Schwarz</author>
    <author>Reiner Creutzburg</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>3155</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>350-1</pageFirst>
    <pageLast>350-14</pageLast>
    <pageNumber>14</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName>Society for Imaging Science and Technology</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2024-02-26</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">iPhone12 imagery in scene-referred computer graphics pipelines</title>
    <abstract language="eng">With the release of the Apple iPhone 12 Pro Max in 2020, various features were integrated that make it attractive as a recording device for scene-related computer graphics pipelines. The captured Apple RAW images have a much higher dynamic range than the standard 8-bit images. Since a scene-based workflow naturally has an extended dynamic range (HDR), the Apple RAW recordings can be well integrated. To correctly integrate the iPhone 12 pro Apple RAW data into a scene-related workflow, two command-line software solutions, among others, are dcraw and rawtoaces. In this paper, we concentrate on dcraw. dcraw offers the possibility to export RAW images directly to ACES2065-1. Different images recorded under different lighting conditions are examined to determine which options for the dcraw development produce the best results. Images from five different lighting situations like D65, D60, D55, D50, and 2980K, are examined. The DNG files are developed using different methods within dcraw. The values of the recorded ColorChecker24 patches are compared to reference values derived from BabelColor [1] and ACES [2].</abstract>
    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="doi">10.2352/EI.2023.35.3.MOBMU-350</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Eberhard Hasche</author>
    <author>Oliver Karaschewski</author>
    <author>Reiner Creutzburg</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>3156</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>368-1</pageFirst>
    <pageLast>368-15</pageLast>
    <pageNumber>15</pageNumber>
    <edition/>
    <issue/>
    <volume>35</volume>
    <type>article</type>
    <publisherName>Society for Imaging Science and Technology</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2024-02-27</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A qualitative study of LiDAR technologies and their application areas</title>
    <abstract language="eng">In this work, the most relevant 3D LiDAR technologies and their applications in 2022 were investigated. For this purpose, applications of LiDAR systems were classified into the typical application areas "3D modeling", "smart city", "robotics", "smart automotive" and "consumer goods". The investigation has shown that neither "mechanical" LiDAR technologies, nor so-called solid-state LiDAR technologies, nor "hybrid" LiDAR technologies can be evaluated as optimal for the typical application areas. In none of the application areas could all of the elaborated requirements be met. However, the "hybrid" LiDAR technologies such as sequential MEMS LiDAR technology and sequential flash LiDAR technology proved to be among the most suitable for most typical application areas. However, other technologies also tended to be suitable for individual typical application areas. Finally, it was found that several of the LiDAR technologies investigated are currently equally suitable for some typical application areas. To evaluate the suitability, concrete LiDAR systems - of different technologies and properties - were compared with the specific requirements of exemplary applications of an application area. The results of the investigation provide an orientation as to which LiDAR technology is promising for which application area.</abstract>
    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="doi">10.2352/EI.2023.35.3.MOBMU-368</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Daniel Jaster</author>
    <author>Reiner Creutzburg</author>
    <author>Eberhard Hasche</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>2993</id>
    <completedYear>2022</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>401 - 1</pageFirst>
    <pageLast>401 - 9</pageLast>
    <pageNumber>9</pageNumber>
    <edition/>
    <issue>3</issue>
    <volume/>
    <type>article</type>
    <publisherName>Society for Imaging Science and Technology (IS&amp;T)</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2023-12-14</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Application scenarios and usability for modern 360 degree video projection rooms in the MICE industry</title>
    <abstract language="eng">360-degree image and movie content has gained popularity over the media and the MICE (Meeting, Incentive, Conventions, and Exhibitions) industry in the last few years. There are three main reasons for this development. First, on the one hand, it is the immersive character of this media form, and, on the other hand, the development of recording and presentation technology has made significant progress in terms of resolution and quality. Third, after a decade of dynamic rising, the MICE Industry focuses on a disruptive change for more digital-based solutions. 360-degree panoramas are particularly widespread in VR and AR technology. However, despite the high immersive potential, these forms of presentation have the disadvantage that the users are isolated and have no social contact during the performance. Therefore, efforts have been made to project 360-degree content in specially equipped rooms or planetariums to enable a shared experience for the audience. One application area for 360-degree panoramas and films is conference rooms in hotels, conference centers, and any other venues that create an immersive environment for their clients to stimulate creativity. This work aims to overview the various application scenarios and usability possibilities for such conference rooms. In particular, we consider applications in construction, control, tourism, medicine, art exhibition, architecture, music performance, education, partying, organizing and carrying out events, and video conferencing. These applications and use scenarios were successfully tested, implemented, and evaluated in the 360-degree conference room “Dortmund” in the Hotel Park Soltau in Soltau, Germany. Finally, the advantages, challenges, and limitations of the proposed method are described.</abstract>
    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="url">https://library.imaging.org/ei/articles/34/3/MOBMU-401</identifier>
    <identifier type="doi">10.2352/EI.2022.34.3.MOBMU-401</identifier>
    <identifier type="issn">2470-1173</identifier>
    <note>Band:34</note>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Reiner Creutzburg</author>
    <author>Dirk Hagen</author>
    <author>Eberhard Hasche</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>2994</id>
    <completedYear>2022</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>13</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>SPIE - The International Society for Optics and Photonics</publisherName>
    <publisherPlace>Orlando, United States</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2023-12-14</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Application scenarios and usability for modern 360 degree video projection rooms in modern meeting, incentive, conventions, and exhibitions (MICE) industry</title>
    <parentTitle language="eng">Konferenz: SPIE Defence and Commercial Sensing Industry, Orlando, United States, 2022/ Band: PROCEEDINGS VOLUME PC12100 SPIE DEFENSE + COMMERCIAL SENSING | 3 APRIL - 13 JUNE 2022 Multimodal Image Exploitation and Learning 2022</parentTitle>
    <identifier type="isbn">978-1-5106-5617-8</identifier>
    <identifier type="url">https://www.spiedigitallibrary.org/conference-proceedings-of-spie/PC12100/2618848/Application-scenarios-and-usability-for-modern-360-degree-video-projection/10.1117/12.2618848.full</identifier>
    <identifier type="doi">10.1117/12.2618848</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Reiner Creutzburg</author>
    <author>Dirk Hagen</author>
    <author>Eberhard Hasche</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
  </doc>
  <doc>
    <id>2992</id>
    <completedYear>2022</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>12</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>SPIE - The International Society for Optics and Photonics</publisherName>
    <publisherPlace>Orlando, United States</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2023-12-14</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Potentials and challenges for mega events: mobile devices usability for virtual reality, augmented reality, and visual effects</title>
    <parentTitle language="eng">Konferenz: Multimodal Image Exploitation and Learning 2022, Orlando, United States, 2022/ Koferenzband: Multimodal Image Exploitation and Learning 2022</parentTitle>
    <identifier type="isbn">978-1-5106-5617-8</identifier>
    <identifier type="url">https://www.spiedigitallibrary.org/conference-proceedings-of-spie/PC12100/2618822/Potentials-and-challenges-for-mega-events--mobile-devices-usability/10.1117/12.2618822.full</identifier>
    <identifier type="doi">10.1117/12.2618822</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Reiner Creutzburg</author>
    <author>Dirk Hagen</author>
    <author>Eberhard Hasche</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
  </doc>
  <doc>
    <id>2991</id>
    <completedYear>2022</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>400-1</pageFirst>
    <pageLast>400-13</pageLast>
    <pageNumber>13</pageNumber>
    <edition/>
    <issue>34</issue>
    <volume/>
    <type>article</type>
    <publisherName>Society for Imaging Science and Technology</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2023-12-14</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">RAW images and videos for 30K panoramic projection using the ACES workflow</title>
    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="url">https://library.imaging.org/ei/articles/34/3/MOBMU-400</identifier>
    <identifier type="doi">10.2352/EI.2022.34.3.MOBMU-400</identifier>
    <identifier type="issn">2470-1173</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Keine Nutzungslizenz vergeben - es gilt das deutsche Urheberrecht</licence>
    <author>Eberhard Hasche</author>
    <author>Oliver Karaschewski</author>
    <author>Reiner Creutzburg</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>2761</id>
    <completedYear>2021</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>375</pageFirst>
    <pageLast>388</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>Bonn</publisherName>
    <publisherPlace>Gesellschaft für Informatik</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-02-01</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
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      <type>uncontrolled</type>
      <value>Data Science</value>
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    <subject>
      <language>eng</language>
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      <language>eng</language>
      <type>uncontrolled</type>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Region Poposal</value>
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    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="doi">10.2352/ISSN.2470-1173.2021.3.MOBMU-039</identifier>
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    <author>Raunak Suryawanshi</author>
    <author>Gnana Swaroop Kishnamurthy</author>
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    <author>Michael Hartmann</author>
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    <parentTitle language="eng">Electronic Imaging</parentTitle>
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    <author>Saiful Islam</author>
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    <author>Goran Rafajlovski</author>
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    <author>Reiner Creutzburg</author>
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      <value>mobility</value>
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      <value>sustainability</value>
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    <id>2714</id>
    <completedYear>2021</completedYear>
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    <language>eng</language>
    <pageFirst>135-1</pageFirst>
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    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="doi">10.2352/ISSN.2470-1173.2021.3.MOBMU-135</identifier>
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    <author>Franziska Schwarz</author>
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    <author>Reiner Creutzburg</author>
    <author>David Akopian</author>
    <subject>
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      <type>uncontrolled</type>
      <value>cybersecurity</value>
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      <value>router forensics</value>
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    <subject>
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      <value>router security</value>
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      <type>uncontrolled</type>
      <value>smart home</value>
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      <value>smart home devices</value>
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  <doc>
    <id>2713</id>
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    <language>eng</language>
    <pageFirst>38-1</pageFirst>
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    <author>Lukasz Rojek</author>
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    <author>Reiner Creutzburg</author>
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      <language>deu</language>
      <type>uncontrolled</type>
      <value>real-time</value>
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      <language>deu</language>
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      <value>smart energy house</value>
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  <doc>
    <id>2704</id>
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    <language>eng</language>
    <pageFirst>143-1</pageFirst>
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    <parentTitle language="eng">Electronic Imaging</parentTitle>
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    <author>Uduak Bassey</author>
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    <author>Reiner Creutzburg</author>
    <author>Arne Volland</author>
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      <type>uncontrolled</type>
      <value>identification</value>
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      <language>eng</language>
      <type>uncontrolled</type>
      <value>near-infrared</value>
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      <type>uncontrolled</type>
      <value>plasics</value>
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      <type>uncontrolled</type>
      <value>pyrolysis</value>
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      <language>eng</language>
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      <value>separation</value>
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      <type>uncontrolled</type>
      <value>spectroscopy</value>
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    <subject>
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      <type>uncontrolled</type>
      <value>wasre sorting</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>waste2energy</value>
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    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
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  <doc>
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    <completedYear>2021</completedYear>
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    <language>eng</language>
    <pageFirst>74-1</pageFirst>
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    <identifier type="doi">10.2352/ISSN.2470-1173.2021.3.MOBMU-074</identifier>
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    <author>Maximilian Richter</author>
    <author>Klaus Schwarz</author>
    <author>Reiner Creutzburg</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Blue Team</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Censys</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Maltego</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>OSINT</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Red Team</value>
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      <language>eng</language>
      <type>uncontrolled</type>
      <value>Shodan</value>
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      <type>uncontrolled</type>
      <value>cybersecurity</value>
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      <value>open source intelligence</value>
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  <doc>
    <id>2702</id>
    <completedYear>2021</completedYear>
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    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>136-1</pageFirst>
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    <title language="eng">Improving Detection of Manipulated Passport Photos - Train- ing Course for Border Control Inspectors to Detect Morphed Facial Passport Photos - Part I: Introduction, State-of-the-Art and Preparatory Tests and Experiments</title>
    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="doi">10.2352/ISSN.2470-1173.2021.3.MOBMU-136</identifier>
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    <author>Franziska Schwarz</author>
    <author>Klaus Schwarz</author>
    <author>Reiner Creutzburg</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>border control</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>face morphing</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>homeland security</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>image forensic</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>image morphing</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>passport control</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>passport photo manipulation</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>security</value>
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    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
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  <doc>
    <id>2701</id>
    <completedYear>2021</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>108-1</pageFirst>
    <pageLast>108-14</pageLast>
    <pageNumber/>
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    <title language="eng">Using ACES Look Modification Transforms (LMTs) in VFX Environments – Part 2: Gamut Mapping</title>
    <parentTitle language="eng">Electronic Imaging</parentTitle>
    <identifier type="doi">10.2352/ISSN.2470-1173.2021.3.MOBMU-108</identifier>
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    <licence>Keine Nutzungslizenz vergeben - es gilt das deutsche Urheberrecht</licence>
    <author>Eberhard Hasche</author>
    <author>Oliver Karaschewski</author>
    <author>Reiner Creutzburg</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>3ARRI footage</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>ACES</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>VFX</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>color gamut</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>color management</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>color spaces</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>tone mapping</value>
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    <collection role="ddc" number="006">Spezielle Computerverfahren</collection>
    <collection role="open_access" number="">open_access</collection>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
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  <doc>
    <id>2700</id>
    <completedYear>2021</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>45-1</pageFirst>
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    <pageNumber/>
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    <issue/>
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