Zida Song

Computer Vision and Pattern Recognition · 2022

A researcher in the Science corpus: 1 paper; trusts 93 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 53 citations into it
• Artificial Intelligence — 19 citations into it

Whom Zida Song trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Alex Krizhevsky
4. David G. Lowe
5. Geoffrey E. Hinton
6. Shaoqing Ren
7. Piotr Doll'ar
8. Ilya Sutskever
9. Pedro F. Felzenszwalb
10. Yann LeCun

Papers from Zida Song's perspective

Ordered by how strongly the researchers Zida Song 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. ImageNet: A large-scale hierarchical image database
4. Gradient-based learning applied to document recognition
5. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
6. GENERATIVE ADVERSARIAL NETS
7. Microsoft COCO: Common Objects in Context
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Long Short-Term Memory

Their papers

• A Survey of the Four Pillars for Small Object Detection: Multiscale Representation, Contextual Information, Super-Resolution, and Region Proposal (2022) — 306 citations