Wei-Long Zheng
Cognitive Neuroscience · 2014–2021
A researcher in the Science corpus: 6 papers; trusts 37 researchers and is trusted by 50 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 66 citations into it; #544 of 10,852 by trust here, #2,220 by citations
- Experimental and Cognitive Psychology — 65 citations into it; #382 of 9,731 by trust here, #1,540 by citations
- Artificial Intelligence — 29 citations into it
- Social Psychology — 21 citations into it
- Computer Vision and Pattern Recognition — 17 citations into it
- Signal Processing — 15 citations into it
- Human-Computer Interaction — 12 citations into it
- Cardiology and Cardiovascular Medicine — 8 citations into it; #14 of 906 by trust here, #337 by citations
Whom Wei-Long Zheng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Bao-Liang Lu
- Mohammad Soleymani
- Geoffrey E. Hinton
- Jia-Yi Zhu
- Li-Chen Shi
- Chih-Jen Lin
- Mu Li
- Vladimir Naumovich Vapni
- Xiao-Wei Wang
- Dan Nie
Who trusts Wei-Long Zheng overall
- Wei Liu
- Jinpeng Li
- Bao-Liang Lu
- Xiang Li
- Yitong Li
- Dongrui Wu
- Wenming Zheng
- Tengfei Song
- Yonghao Song
- Peixiang Zhong
Papers from Wei-Long Zheng's perspective
Ordered by how strongly the researchers Wei-Long Zheng 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Comparing Recognition Performance and Robustness of Multimodal Deep Learning Models for Multimodal Emotion Recognition (2021) — 424 citations
- EmotionMeter: A Multimodal Framework for Recognizing Human Emotions (2019) — 1,124 citations
- Identifying Stable Patterns over Time for Emotion Recognition from EEG (2016) — 880 citations
- A multimodal approach to estimating vigilance using EEG and forehead EOG (2016) — 385 citations
- Investigating Critical Frequency Bands and Channels for EEG-Based Emotion Recognition with Deep Neural Networks (2015) — 2,280 citations
- EEG-based emotion classification using deep belief networks (2014) — 327 citations