A. D. Souza
Computer Vision and Pattern Recognition · with Oliveira-Santos · 2009–2020
A researcher in the Science corpus: 5 papers; trusts 129 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 97 citations into it
- Aerospace Engineering — 27 citations into it
- Artificial Intelligence — 19 citations into it
- Model Architectures — 6 citations into it
- Optimization & Training — 5 citations into it
Whom A. D. Souza trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- L. Eon Bottou
- Kaiming He
- Geoffrey E. Hinton
- Ross B. Girshick
- Yoshua Bengio
- Alex Krizhevsky
- Yann LeCun
- Frank Tong
- Ilya Sutskever
- Nitish Srivastava
Who trusts A. D. Souza overall
Papers from A. D. Souza's perspective
Ordered by how strongly the researchers A. D. Souza trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Going deeper with convolutions
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Prediction-based portfolio optimization model using neural networks (2009) — 165 citations
- Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection (2020) — 469 citations
- PolyLaneNet: Lane Estimation via Deep Polynomial Regression (2020) — 377 citations
- Self-Driving Cars: A Survey (2019) — 1,226 citations
- Facial expression recognition with Convolutional Neural Networks: Coping with few data and the training sample order (2017) — 730 citations