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pro vyhledávání: '"Vandersteegen, Maarten"'
Autor:
Van Delm, Josse, Vandersteegen, Maarten, Burrello, Alessio, Sarda, Giuseppe Maria, Conti, Francesco, Pagliari, Daniele Jahier, Benini, Luca, Verhelst, Marian
Publikováno v:
2023 60th ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, USA, 2023, pp. 1-6
Optimal deployment of deep neural networks (DNNs) on state-of-the-art Systems-on-Chips (SoCs) is crucial for tiny machine learning (TinyML) at the edge. The complexity of these SoCs makes deployment non-trivial, as they typically contain multiple het
Externí odkaz:
http://arxiv.org/abs/2406.07453
Detecting persons in images or video with neural networks is a well-studied subject in literature. However, such works usually assume the availability of a camera of decent resolution and a high-performance processor or GPU to run the detection algor
Externí odkaz:
http://arxiv.org/abs/2212.08415
Using hand gestures to answer a call or to control the radio while driving a car, is nowadays an established feature in more expensive cars. High resolution time-of-flight cameras and powerful embedded processors usually form the heart of these gestu
Externí odkaz:
http://arxiv.org/abs/2004.11623
Drones have proven to be useful in many industry segments such as security and surveillance, where e.g. on-board real-time object tracking is a necessity for autonomous flying guards. Tracking and following suspicious objects is therefore required in
Externí odkaz:
http://arxiv.org/abs/1904.02024
Autor:
Vandersteegen, Maarten
Deep learning has forever shaped the field of computer vision applications. Solving computer vision tasks with this technology, has proven to outperform traditional (partially) hand-crafted algorithms in many technical fields. However, the large comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1131::a96332edd86e7603e0cbf118397779a7
https://lirias.kuleuven.be/handle/20.500.12942/718530
https://lirias.kuleuven.be/handle/20.500.12942/718530
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