Ning Jin
Computer Vision and Pattern Recognition · with Bohg · 2019
A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 8 citations into it
- Artificial Intelligence — 6 citations into it
- Control and Systems Engineering — 6 citations into it
Whom Ning Jin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Ning Jin's perspective
Ordered by how strongly the researchers Ning Jin trusts endorse each paper. Same corpus, a different order for every researcher.
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Self-Supervised Learning of State Estimation for Manipulating Deformable Linear Objects (2019) — 184 citations