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ORCIDMulti-faceted Deep Learning, 2021
- Jenny Benois-Pineau, Akka Zemmari:
Multi-faceted Deep Learning - Models and Data. Springer 2021, ISBN 978-3-030-74477-9 - Jenny Benois-Pineau:
Introduction. 1-3 - Akka Zemmari, Jenny Benois-Pineau:
Deep Neural Networks: Models and Methods. 5-38 - Alexandre Benoît, Badih Ghattas, Emna Amri, Joris Fournel, Patrick Lambert:
Deep Learning for Semantic Segmentation. 39-72 - Nicolas Thome:
Beyond Full Supervision in Deep Learning. 73-101 - Stefan Duffner, Christophe Garcia, Khalid Idrissi, Atilla Baskurt:
Similarity Metric Learning. 103-125 - Yannick Le Cacheux, Hervé Le Borgne, Michel Crucianu:
Zero-Shot Learning with Deep Neural Networks for Object Recognition. 127-150 - Danny Francis
, Benoit Huet:
Image and Video Captioning Using Deep Architectures. 151-174 - Ofer Hadar, Raz Birman:
Deep Learning in Video Compression Algorithms. 175-198 - Pierre-Etienne Martin, Jenny Benois-Pineau, Renaud Péteri, Akka Zemmari, Julien Morlier:
3D Convolutional Networks for Action Recognition: Application to Sport Gesture Recognition. 199-229 - Geoffroy Peeters, Gaël Richard:
Deep Learning for Audio and Music. 231-266 - Pascal Bourdon, Olfa Ben Ahmed, Thierry Urruty, Khalifa Djemal, Christine Fernandez-Maloigne:
Explainable AI for Medical Imaging: Knowledge Matters. 267-292 - Leonardo Galteri, Lorenzo Seidenari, Tiberio Uricchio, Marco Bertini, Alberto Del Bimbo:
Improving Video Quality with Generative Adversarial Networks. 293-314 - Jenny Benois-Pineau, Akka Zemmari:
Conclusion. 315-316
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