The Contribution of AI to neurological analysis of eye movements
Various deep network architectures have been proposed in the literature to handle a wide variety of sensory data ranging from simple 1-D signals and text to ...
Multimodal deep learning for audiovisual productionPerception plays a critical role in autonomous driving, encompassing key areas such as place recognition, semantic segmentation, and object detection. Optimizing Neural Networks for TinyML: a study on quantization ...Action recognition by learning deep multi-granular spatio-temporal video ... recognition module is a multi-model network called the M-3D network. This ... High-Throughput Deep Learning Inference at the Hybrid Mobile EdgeLoss functions are at the heart of deep learning, shaping how models learn and perform across diverse tasks. They are used to quantify the ...
Autres Cours:
