Zixing Zhang
Signal Processing · 2013–2019
A researcher in the Science corpus: 5 papers; trusts 70 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Signal Processing — 104 citations into it; #5,642 of 7,572 by trust here, #2,001 by citations
- Artificial Intelligence — 100 citations into it; #26,831 of 35,345 by trust here, #14,181 by citations
- Speech & Audio — 47 citations into it
- Computer Vision and Pattern Recognition — 36 citations into it
- Model Architectures — 25 citations into it
- Natural Language Processing — 23 citations into it
- Computational Mechanics — 18 citations into it
- Representation & Self-Supervised Learning — 14 citations into it
Whom Zixing Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Graves
- Yann LeCun
- Alex Krizhevsky
- Sepp Hochreiter
- Diederik P. Kingma
- J. Urgen Schmidhuber
- Ilya Sutskever
- Kaiming He
Who trusts Zixing Zhang overall
- Nantheera Anantrasirichai
- Xiangang Li
- Chunwei Tian
- D. Bull
- Qi-rong Mao
- Jun Deng
- Zhuo Chen
- Frank Emmert-Streib
- Bin Guo
Papers from Zixing Zhang's perspective
Ordered by how strongly the researchers Zixing Zhang 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Robust speech recognition using long short-term memory recurrent neural networks for hybrid acoustic modelling (2014) — 75 citations
- Exploiting time-frequency patterns with LSTM-RNNs for low-bitrate audio restoration (2019) — 39 citations
- Deep Learning for Environmentally Robust Speech Recognition (2017) — 344 citations
- Introducing shared-hidden-layer autoencoders for transfer learning and their application in acoustic emotion recognition (2014) — 73 citations
- Sparse Autoencoder-Based Feature Transfer Learning for Speech Emotion Recognition (2013) — 362 citations