Ziming Zhang
Computer Vision and Pattern Recognition · with Saligrama · 2011–2020
A researcher in the Science corpus: 7 papers; trusts 1,024 researchers and is trusted by 1,053 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 195 citations into it; #1,278 of 21,575 by trust here, #3,111 by citations
- Artificial Intelligence — 122 citations into it; #1,594 of 35,345 by trust here, #6,064 by citations
- Representation & Self-Supervised Learning — 44 citations into it; #1,383 of 3,145 by trust here, #2,587 by citations
- Evaluation & Benchmarks — 27 citations into it
- Radiology, Nuclear Medicine and Imaging — 18 citations into it
- Multimodal Learning — 16 citations into it
- Model Architectures — 15 citations into it
- Meta & Continual Learning — 9 citations into it
Whom Ziming Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Karen Simonyan
- Andrew Zisserman
- Ross B. Girshick
- Kaiming He
- Yoshua Bengio
- Ilya Sutskever
- Diederik P. Kingma
- Yann LeCun
Who trusts Ziming Zhang overall
- Soravit Changpinyo
- Vinay Kumar Verma
- Wei-Lun Chao
- Yongqin Xian
- Tao A. Xiang
- Max Bucher
- Shafin Rahman
- Anjan Dutta
- Li Zhang
- Guosen Xie
Papers from Ziming Zhang's perspective
Ordered by how strongly the researchers Ziming Zhang trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Zero-Shot Learning via Semantic Similarity Embedding (2015) — 649 citations
- BING: Binarized normed gradients for objectness estimation at 300fps (2014) — 783 citations
- Zero-Shot Learning via Joint Latent Similarity Embedding (2015) — 363 citations
- Attention-Based Multimodal Fusion for Video Description (2017) — 397 citations
- Zero-Shot Recognition via Structured Prediction (2016) — 99 citations
- Proposal generation for object detection using cascaded ranking SVMs (2011) — 115 citations
- Advancing Biosensors with Machine Learning. (2020) — 573 citations