Gradient-Based Localization and Spatial Attention for Confidence Measure in Fine-Grained Recognition using Deep Neural Networks

Charles A. Kantor, Léonard Boussioux, Brice Rauby, Hugues Talbot. Gradient-Based Localization and Spatial Attention for Confidence Measure in Fine-Grained Recognition using Deep Neural Networks. In Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021. pages 15807-15808, AAAI Press, 2021. [doi]

@inproceedings{KantorBRT21a,
  title = {Gradient-Based Localization and Spatial Attention for Confidence Measure in Fine-Grained Recognition using Deep Neural Networks},
  author = {Charles A. Kantor and Léonard Boussioux and Brice Rauby and Hugues Talbot},
  year = {2021},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/17900},
  researchr = {https://researchr.org/publication/KantorBRT21a},
  cites = {0},
  citedby = {0},
  pages = {15807-15808},
  booktitle = {Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021},
  publisher = {AAAI Press},
  isbn = {978-1-57735-866-4},
}