@inproceedings{VriesmanBrittoJuniorZimmeretal.2020, author = {Vriesman, Daniel and Britto Junior, Alceu and Zimmer, Alessandro and Koerich, Alessandro Lameiras}, title = {Texture CNN for thermoelectric metal pipe image classification}, booktitle = {2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI)}, publisher = {IEEE}, address = {Piscataway}, issn = {2375-0197}, doi = {https://doi.org/10.1109/ICTAI.2019.00085}, pages = {569 -- 574}, year = {2020}, language = {en} } @article{VriesmanBrittoJuniorZimmeretal.2019, author = {Vriesman, Daniel and Britto Junior, Alceu and Zimmer, Alessandro and Koerich, Alessandro Lameiras and Paludo, Rodrigo}, title = {Automatic visual inspection of thermoelectric metal pipes}, volume = {13}, journal = {Signal, Image and Video Processing}, number = {5}, publisher = {Springer}, address = {London}, issn = {1863-1711}, doi = {https://doi.org/10.1007/s11760-019-01435-2}, pages = {975 -- 983}, year = {2019}, language = {en} } @unpublished{PederivaDeMartinoZimmer2023, author = {Pederiva, Marcelo Eduardo and De Martino, Jos{\´e} Mario and Zimmer, Alessandro}, title = {MonoNext: A 3D Monocular Object Detection with ConvNext}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2308.00596}, year = {2023}, abstract = {Autonomous driving perception tasks rely heavily on cameras as the primary sensor for Object Detection, Semantic Segmentation, Instance Segmentation, and Object Tracking. However, RGB images captured by cameras lack depth information, which poses a significant challenge in 3D detection tasks. To supplement this missing data, mapping sensors such as LIDAR and RADAR are used for accurate 3D Object Detection. Despite their significant accuracy, the multi-sensor models are expensive and require a high computational demand. In contrast, Monocular 3D Object Detection models are becoming increasingly popular, offering a faster, cheaper, and easier-to-implement solution for 3D detections. This paper introduces a different Multi-Tasking Learning approach called MonoNext that utilizes a spatial grid to map objects in the scene. MonoNext employs a straightforward approach based on the ConvNext network and requires only 3D bounding box annotated data. In our experiments with the KITTI dataset, MonoNext achieved high precision and competitive performance comparable with state-of-the-art approaches. Furthermore, by adding more training data, MonoNext surpassed itself and achieved higher accuracies.}, language = {en} } @inproceedings{LugnerVriesmanInderstetal.2021, author = {Lugner, Robert and Vriesman, Daniel and Inderst, Maximilian and Sequeira, Gerald Joy and Pasupuleti, Niyathipriya and Zimmer, Alessandro and Brandmeier, Thomas}, title = {Evaluation of sensor tolerances and inevitability for pre-crash safety systems in real case scenarios}, booktitle = {2020 IEEE 3rd Connected and Automated Vehicles Symposium (CAVS)}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-7281-9001-3}, doi = {https://doi.org/10.1109/CAVS51000.2020.9334578}, year = {2021}, language = {en} } @inproceedings{VriesmanPederivaDeMartinoetal.2021, author = {Vriesman, Daniel and Pederiva, Marcelo Eduardo and De Martino, Jos{\´e} Mario and Britto Junior, Alceu and Zimmer, Alessandro and Brandmeier, Thomas}, title = {A fusion approach for pre-crash scenarios based on lidar and camera sensors}, booktitle = {2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)}, publisher = {IEEE}, address = {Piscataway (NJ)}, isbn = {978-1-7281-8964-2}, doi = {https://doi.org/10.1109/VTC2021-Spring51267.2021.9449039}, year = {2021}, language = {en} } @inproceedings{LopesdaSilvaTabataCardosoBrotoetal.2020, author = {Lopes da Silva, Joed and Tabata, Alan Naoto and Cardoso Broto, Lucas and Pereira Cocron, Marta and Zimmer, Alessandro and Brandmeier, Thomas}, title = {Open source multipurpose multimedia annotation tool}, booktitle = {Image Analysis and Recognition}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-50346-8}, issn = {0302-9743}, doi = {https://doi.org/10.1007/978-3-030-50347-5_31}, pages = {356 -- 367}, year = {2020}, language = {en} } @inproceedings{ChanZimmerLopesdaSilvaetal.2020, author = {Chan, Lap Yan and Zimmer, Alessandro and Lopes da Silva, Joed and Brandmeier, Thomas}, title = {European Union dataset and annotation tool for real time automatic license plate detection and blurring}, booktitle = {2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, doi = {https://doi.org/10.1109/ITSC45102.2020.9294240}, year = {2020}, language = {en} } @inproceedings{VriesmanThoereszSteinhauseretal.2020, author = {Vriesman, Daniel and Th{\"o}resz, Bernhard and Steinhauser, Dagmar and Zimmer, Alessandro and Britto Junior, Alceu and Brandmeier, Thomas}, title = {An Experimental Analysis of Rain Interference on Detection and Ranging Sensors Signals considering the Near Field}, booktitle = {2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-4149-7}, doi = {https://doi.org/10.1109/ITSC45102.2020.9294505}, year = {2020}, language = {en} } @article{BrunetiSeverinoZimmerBrandmeieretal.2019, author = {Bruneti Severino, Jo{\~a}o Victor and Zimmer, Alessandro and Brandmeier, Thomas and Zanetti Freire, Roberto}, title = {Pedestrian recognition using micro Doppler effects of radar signals based on machine learning and multi-objective optimization}, volume = {2019}, journal = {Expert Systems with Applications}, number = {136}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0957-4174}, doi = {https://doi.org/10.1016/j.eswa.2019.06.048}, pages = {304 -- 315}, year = {2019}, language = {en} } @inproceedings{CardosoBrotoOkimotoPereiraCocronetal.2020, author = {Cardoso Broto, Lucas and Okimoto, Maria L.R. and Pereira Cocron, Marta and Zimmer, Alessandro and Brandmeier, Thomas}, title = {Application of Low-cost Pulse Radar for Heart Rate Detection in Vehicle Interior}, booktitle = {Sensors and Electronic Instrumentation Advances: Proceedings of the 6th International Conference on Sensors and Electronic Instrumentation Advances and Frequency \& Time: Proceedings of the 2nd IFSA Frequency \& Time Conference}, editor = {Yurish, Sergey Y.}, publisher = {IFSA}, address = {Castelldefels}, isbn = {978-84-09-23483-7}, url = {https://www.seia-conference.com/publications.html}, pages = {99 -- 104}, year = {2020}, language = {en} }