Ashish Khanna

Computer Vision and Pattern Recognition · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 121 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 39 citations into it
• Artificial Intelligence — 27 citations into it; #33,118 of 35,345 by trust here, #27,551 by citations
• Model Architectures — 13 citations into it
• Optimization & Training — 7 citations into it

Whom Ashish Khanna trusts overall

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

1. Kaiming He
2. Diederik P. Kingma
3. Ross B. Girshick
4. Alex Krizhevsky
5. Geoffrey E. Hinton
6. Karen Simonyan
7. Yann LeCun
8. Yoshua Bengio
9. Jimmy Ba
10. Andrew Zisserman

Who trusts Ashish Khanna overall

1. Fatemeh Haghighat

Papers from Ashish Khanna's perspective

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

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

Their papers

• CovidGAN: Data Augmentation Using Auxiliary Classifier GAN for Improved Covid-19 Detection (2020) — 648 citations
• An optimized dense convolutional neural network model for disease recognition and classification in corn leaf (2020) — 312 citations
• Identifying pneumonia in chest X-rays: A deep learning approach (2019) — 434 citations