Fang Liu
Computer Vision and Pattern Recognition · IEEE Access · 2014–2021
A researcher in the Science corpus: 5 papers; trusts 483 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 194 citations into it
- Artificial Intelligence — 98 citations into it; #21,981 of 35,345 by trust here, #21,878 by citations
- Computational Theory and Mathematics — 28 citations into it; #7,386 of 12,182 by trust here, #5,465 by citations
- Model Architectures — 13 citations into it
Whom Fang Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ross B. Girshick
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Kalyanmoy Deb
- Karen Simonyan
- Qingfu Zhang
- Yann LeCun
- Andrew Zisserman
- Yoshua Bengio
Who trusts Fang Liu overall
Papers from Fang Liu's perspective
Ordered by how strongly the researchers Fang Liu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- 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
- Residual Spectral-Spatial Attention Network for Hyperspectral Image Classification (2021) — 438 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