Prabir Kumar Biswas

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 2 papers; trusts 282 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 72 citations into it
• Generative Models — 45 citations into it
• Artificial Intelligence — 17 citations into it
• Model Architectures — 5 citations into it

Whom Prabir Kumar Biswas trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Kaiming He
6. Yann LeCun
7. Sergey Ioffe
8. Christian Szegedy
9. Ilya Sutskever
10. Jimmy Ba

Papers from Prabir Kumar Biswas's perspective

Ordered by how strongly the researchers Prabir Kumar Biswas trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. GENERATIVE ADVERSARIAL NETS
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Prior Guided GAN Based Semantic Inpainting (2020) — 101 citations
• Improving Consistency and Correctness of Sequence Inpainting using Semantically Guided Generative Adversarial Network (2017) — 10 citations