L. Jiao

Computer Vision and Pattern Recognition · Evolutionary Computation · 2000–2021

A researcher in the Science corpus: 17 papers; trusts 835 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 282 citations into it; #14,701 of 21,575 by trust here, #8,502 by citations
• Artificial Intelligence — 164 citations into it; #12,043 of 35,345 by trust here, #11,750 by citations
• Computational Theory and Mathematics — 68 citations into it; #3,956 of 12,182 by trust here, #2,851 by citations
• Control and Systems Engineering — 34 citations into it; #3,465 of 8,257 by trust here, #2,782 by citations
• Media Technology — 34 citations into it; #2,893 of 3,621 by trust here, #1,329 by citations
• Model Architectures — 18 citations into it
• Representation & Self-Supervised Learning — 17 citations into it
• Evaluation & Benchmarks — 14 citations into it

Whom L. Jiao trusts overall

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

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

Who trusts L. Jiao overall

1. Weicai Zhong
2. Ye Tian
3. Shaocheng Tong
4. Huanqing Wang
5. P. Adarsh
6. Yaochu Jin
7. Handing Wang
8. Shouyong Jiang
9. Jing Liu
10. Xing-yi Zhang

Papers from L. Jiao's perspective

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

Their papers

• Two_Arch2: An Improved Two-Archive Algorithm for Many-Objective Optimization (2015) — 500 citations
• MOEA/D with Adaptive Weight Adjustment (2014) — 625 citations
• A Multiobjective Evolutionary Algorithm Based on Decision Variable Analyses for Multiobjective Optimization Problems With Large-Scale Variables (2016) — 441 citations
• A novel genetic algorithm based on immunity (2000) — 470 citations
• Residual Spectral-Spatial Attention Network for Hyperspectral Image Classification (2021) — 438 citations
• Self-Supervised Representation Learning for Remote Sensing Image Change Detection Based on Temporal Prediction (2020) — 65 citations
• New Contour Cue-Based Hybrid Sparse Learning for Salient Object Detection (2019) — 15 citations
• A Survey of Deep Learning-Based Object Detection (2019) — 1,141 citations
• Global Low-Rank Image Restoration With Gaussian Mixture Model (2018) — 24 citations
• Remote Sensing Image Registration With Modified SIFT and Enhanced Feature Matching (2017) — 346 citations
• Change Detection in Synthetic Aperture Radar Images Based on Deep Neural Networks (2016) — 593 citations
• State‐feedback stabilization for a class of stochastic time‐delay nonlinear systems (2012) — 62 citations
• Adaptive NN Backstepping Output-Feedback Control for Stochastic Nonlinear Strict-Feedback Systems With Time-Varying Delays (2010) — 424 citations
• Technical communique: Finite-time stability theorem of stochastic nonlinear systems (2010) — 264 citations
• Multiobjective Immune Algorithm with Nondominated Neighbor-Based Selection (2008) — 474 citations
• Wavelet support vector machine (2004) — 533 citations
• A multiagent genetic algorithm for global numerical optimization (2004) — 315 citations