Zhiming Luo

Computer Vision and Pattern Recognition · 2017–2021

A researcher in the Science corpus: 8 papers; trusts 589 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 156 citations into it; #10,499 of 21,575 by trust here, #5,843 by citations
• Artificial Intelligence — 85 citations into it; #21,382 of 35,345 by trust here, #19,439 by citations
• Representation & Self-Supervised Learning — 45 citations into it
• Media Technology — 27 citations into it; #2,204 of 3,621 by trust here, #1,498 by citations
• Optimization & Training — 18 citations into it
• Model Architectures — 14 citations into it
• Atmospheric Science — 12 citations into it; #2,553 of 4,804 by trust here, #2,243 by citations
• Radiology, Nuclear Medicine and Imaging — 12 citations into it; #2,466 of 3,265 by trust here, #2,321 by citations

Whom Zhiming Luo trusts overall

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

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

Who trusts Zhiming Luo overall

1. Deng-Ping Fan
2. Jing Zhang
3. Jiangjiang Liu
4. Wenguan Wang
5. Thierry Bouwmans
6. Ting Zhao
7. Zhe Wu
8. Swalpa Kumar Roy
9. Youwei Pang
10. Xuebin Qin

Papers from Zhiming Luo's perspective

Ordered by how strongly the researchers Zhiming Luo 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-Identification (2019) — 615 citations
• Neighborhood Contrastive Learning for Novel Class Discovery (2021) — 202 citations
• OpenMix: Reviving Known Knowledge for Discovering Novel Visual Categories in an Open World (2020) — 150 citations
• Non-local Deep Features for Salient Object Detection (2017) — 557 citations
• Weighted Res-UNet for High-Quality Retina Vessel Segmentation (2018) — 978 citations
• Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework (2018) — 1,589 citations
• Manifold regularized discriminative feature selection for multi-label learning (2019) — 327 citations
• Interactive deep learning method for segmenting moving objects (2017) — 317 citations