TY - CHAP A1 - Philipps, Jonathan A1 - Bönninger, Ingrid A1 - Weigert, Martin A1 - Vasquez, Javier T1 - Automatic Tracking and Counting of Moving Objects T2 - IEEE Conferenc on Bio-inspired Intelligence (IWOBI), 2014, Liberia, Costa Rica, 16-18 July 2014 N2 - This work presents the conception and development of a software system to detect, track and count automatically moving objects in videos. The aim of the system is the automatically counting of moving turtles on a beach. To achieve a high recognition rate of the moving objects we consider three segmentation strategies (SubstractionGrayscale, SubstractionBinarization, Substraction Canny), two object identification methods (Grayscale Connected, FelzenwalbHuttenlocher) and two object recognition methods Nearest Object Distance, Certain Recognition Matching. In the preprocessing step of our system we select parameters like the interesting area and the object size. We use the segmentation process for the recognition of potential objects. After the identification of objects as turtles we track their movements. In the last step we count the turtles. In order to have a representative test number of moving objects we use videos with 1661 moving cars. The best results of 98.98 percent we reached with the combination Canny Edge Detection, Grayscale Connected, and Certain Region Matching Strategy. Y1 - 2014 SN - 978-1-4799-6174-0 U6 - https://doi.org/10.1109/IWOBI.2014.6913945 SP - 93 EP - 97 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Kutzner, Tobias A1 - Steinert, Christian A1 - Weigert, Martin A1 - Wälder, Olga A1 - Robel, Karsten A1 - Yan, Alan T1 - Complex Assessments in Mathematics and Computer Science with STACK and VPL T2 - InnoEducaTIC, Las Palmas, Gran Canaria, 2018 N2 - Programming is not complicated and yet many students do not pass the first hurdles. Software is logical, follows clear rules and mathematical laws. Any healthy person with basic literacy, numeracy and writing skills can learn it. Writing a book, painting pictures or other creative challenges are much harder. And yet many fail at comparable competences. Teaching programming skills by listening and reading is not enough. Students need the process of trial and error in order to acquire the skills needed and should be able to learn by them. However, students should be able to work independently on a computer. The problem that the beginners are overwhelmed and the advanced are bored. This is the case especially in computer science. Despite the use of a comfortable Learning Management System (LMS), many tasks have been submitted to paper and PDF at our university so far. Since the available question-types could not cover all possible complex tasks, it was difficult to inspire the lecturers for a complete digitization of their tasks. To be able to automatically evaluate even tasks in mathematics, computer science and related scientific disciplines two modules have been successfully evaluated at our university. This paper presents the use of these Moodle modules STACK and VPL in selected courses in mathematics and computer science and how to randomize tasks. In these modules complex tasks are prepared in such a way that they are still solvable for the students and automatically evaluated by the system, thus could considerably facilitate the work of the lecturers and academic staff. On concrete examples possible solutions are shown. KW - LMS assessment KW - automatic formative assessment KW - education KW - mathematics KW - computer science Y1 - 2018 UR - https://accedacris.ulpgc.es/bitstream/10553/52713/2/49.Complex_assessments_mathematics.pdf SN - 978-84-09-02374-5 SP - 375 EP - 381 PB - Universidad de Las Palmas de Gran Canaria CY - Las Palmas ER - TY - GEN A1 - Reinhardt, Fritjof A1 - Altmann, Olaf A1 - Reichmann, Heinz A1 - Brehme, Stefan A1 - Taganow, Olga A1 - Reschke, Pit A1 - Vogel, Steffen A1 - Weigert, Martin A1 - Priwitzer, Barbara T1 - BNP- und Troponin I-Serumspiegel bei unterschiedlicher Schlaganfallätiologie und –topographie T2 - Aktuelle Neurologie Y1 - 2012 SN - 1438-9428 VL - 39 IS - 4 SP - 168 EP - 173 ER - TY - CHAP A1 - Bönninger, Ingrid A1 - Petzold, Michael A1 - Weigert, Martin T1 - Bildbasierte Analyse von Verkehrssituationen T2 - 10. Wissenschaftstage der Hochschule Lausitz (FH) – University of Applied Sciences, 2010 N2 - Im Rahmen der Studien „Defect Detection Study 21“ und „Dynamic Driving Study 21“ (DDS21) zur Reduzierung von Verkehrsunfällen im 21. Jahrhundert sollen die Möglich- keiten einer Videoauswertung von einer im Fahrzeug angebrachten Kamera untersucht werden. In einer ersten Version sollen nur Videodaten ohne Kenntnis anderer Fahr- zeugdaten dahingehend ausgewertet werden, ob sich fremde Fahrzeuge, deren Größe und relative Geschwindigkeit zum Testfahrzeug ermitteln lassen Y1 - 2010 UR - http://www-docs.b-tu.de/forschung/public/wissenschaftstage/2010/informatik/BoenningerI_Bildbasierte_Analyse_von_Vekehrssituationen.pdf ER - TY - GEN A1 - Hiemann, Rico A1 - Hilger, Nadja A1 - Michel, Jörg A1 - Nitschke, Jörg A1 - Böhm, Alexander A1 - Anderer, Ursula A1 - Weigert, Martin A1 - Sack, Ulrich T1 - Automatic Analysis of Immunofluorescence Patterns of HEp‐2 Cells T2 - Annals of the New York Academy of Sciences N2 - The standard screening test for the recognition of autoimmune diseases is the proof of autoantibodies in serum of patients by indirect immunofluorescence (IIF) based on HEp‐2 cells. Manual evaluation of this test is very subjective, slow, and there are no objective parameters as guidelines available. Interlaboratory tests showed occasionally large deviations in the test evaluation resulting in a high variance of results. The aim of this project is fast, objective, safe, and economical automatic analysis of HEp‐2 IIF patterns. Images of IIF patterns were completely and automatically captured using an inverse motorized fluorescence microscope. Thereby, device‐specific parameters were controlled automatically, too. For fast analysis of IIF patterns new algorithms of image processing were developed. Artifacts were recognized and excluded from analysis by the developed software. Analysis of more than 80,000 images clearly demonstrated full automatization and fast processing of IIF patterns. Additionally serum‐specific fluorescence could be easily distinguished from background. Even very weak but positive patterns can be recognized and used for diagnosis. A detailed separation into different basic patterns is possible. Objective, fast, and disease‐related economical analysis of HEp‐2 immunofluorescence patterns is feasible. The implemented software algorithms allowed a mathematical way of describing IIF patterns and can therefore be a useful tool for the needed standardization process. KW - Autoimmune diagnostics KW - HEp-2 cell KW - Immunofluorescence KW - Automatic analysis KW - Screening Y1 - 2007 U6 - https://doi.org/10.1196/annals.1398.042 SN - 0077-8923 VL - 1109 IS - 1 SP - 358 EP - 371 ER -