Jinchang Ren

Computer Vision and Pattern Recognition · 2010–2019

A researcher in the Science corpus: 8 papers; trusts 138 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 106 citations into it; #11,108 of 21,575 by trust here, #6,206 by citations
• Media Technology — 49 citations into it
• Artificial Intelligence — 38 citations into it; #31,260 of 35,345 by trust here, #30,347 by citations
• Cognitive Neuroscience — 38 citations into it
• Atmospheric Science — 20 citations into it
• Remote Sensing — 20 citations into it; #51 of 95 by trust here, #26 by citations
• Representation & Self-Supervised Learning — 17 citations into it
• Electrical and Electronic Engineering — 14 citations into it

Whom Jinchang Ren trusts overall

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

1. Yoshua Bengio
2. Alex Krizhevsky
3. Yann LeCun
4. David G. Lowe
5. Geoffrey E. Hinton
6. Kaiming He
7. Ruslan Salakhutdinov
8. Pascal Vincent
9. Diederik P. Kingma
10. Ilya Sutskever

Who trusts Jinchang Ren overall

1. Gong Cheng
2. Junwei Han
3. Peicheng Zhou
4. Dina Ahmed Ragab
5. Zikun Liu
6. Xiwen Yao
7. John E. Ball
8. Liangpei Zhang

Papers from Jinchang Ren's perspective

Ordered by how strongly the researchers Jinchang Ren 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Learning Multiple Layers of Features from Tiny Images
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Going deeper with convolutions
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges (2019) — 508 citations
• Breast cancer detection using deep convolutional neural networks and support vector machines (2019) — 420 citations
• Novel segmented stacked autoencoder for effective dimensionality reduction and feature extraction in hyperspectral imaging (2016) — 363 citations
• Object Detection in Optical Remote Sensing Images Based on Weakly Supervised Learning and High-Level Feature Learning (2015)
• Background Prior-Based Salient Object Detection via Deep Reconstruction Residual (2015) — 449 citations
• Classification of Hyperspectral Images by Exploiting Spectral–Spatial Information of Superpixel via Multiple Kernels (2015) — 354 citations
• Medical image analysis with artificial neural networks (2010) — 362 citations
• Strathprints Institutional Repository Shuhui and Ren, Jinchang (2015) Effective and Efficient Midlevel Visual Elements-oriented Land-use Classification Using Vhr Remote Sensing Images. Ieee Transactions on Geoscience and Remote Sensing, 53 (8). Pp. 4238-4249. Issn 0196-2892 Effective and Efficient M