Guansong Pang
Artificial Intelligence · ACM Computing Surveys · 2012–2022
A researcher in the Science corpus: 5 papers; trusts 366 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 172 citations into it; #33,326 of 35,345 by trust here, #15,866 by citations
- Computer Vision and Pattern Recognition — 84 citations into it
- Computer Networks and Communications — 50 citations into it; #9,284 of 9,886 by trust here, #4,405 by citations
- Signal Processing — 31 citations into it; #7,202 of 7,572 by trust here, #4,900 by citations
- Representation & Self-Supervised Learning — 19 citations into it
- Statistics and Probability — 18 citations into it
- Epidemiology — 14 citations into it
- Information Systems — 14 citations into it
Whom Guansong Pang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Yann LeCun
- Kaiming He
- Alex Krizhevsky
- Diederik P. Kingma
- Ilya Sutskever
- Karen Simonyan
- Ross B. Girshick
- Andrew Zisserman
Who trusts Guansong Pang overall
- Hongzuo Xu
- Songqiao Han
- Jianpeng Zhang
- Lukas Ruff
- Chunhua Shen
- Yutong Xie
- Xiyang Hu
- Arman Khadjeh Nassirtoussi
Papers from Guansong Pang's perspective
Ordered by how strongly the researchers Guansong Pang 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Deep Isolation Forest for Anomaly Detection (2022) — 493 citations
- Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning (2021) — 542 citations
- Deep Learning for Anomaly Detection (2020) — 1,385 citations
- Deep Anomaly Detection with Deviation Networks (2019) — 468 citations
- An improved K-nearest-neighbor algorithm for text categorization (2012) — 263 citations