Neelam Tyagi

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 26 citations into it
• Artificial Intelligence — 16 citations into it

Whom Neelam Tyagi trusts overall

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

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

Papers from Neelam Tyagi's perspective

Ordered by how strongly the researchers Neelam Tyagi 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
5. GENERATIVE ADVERSARIAL NETS
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Long Short-Term Memory

Their papers

• Self-derived organ attention for unpaired CT-MRI deep domain adaptation based MRI segmentation (2020) — 13 citations
• Tumor-Aware, Adversarial Domain Adaptation from CT to MRI for Lung Cancer Segmentation (2018) — 200 citations