Seongsin Kim
Computer Vision and Pattern Recognition · 2019
A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 12 citations into it
- Civil and Structural Engineering — 10 citations into it
- Mechanics of Materials — 7 citations into it
- Computational Theory and Mathematics — 6 citations into it
Whom Seongsin Kim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Seongsin Kim's perspective
Ordered by how strongly the researchers Seongsin Kim trusts endorse each paper. Same corpus, a different order for every researcher.
- GENERATIVE ADVERSARIAL NETS
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Unsupervised Representation Learning with Deep Convolutional Generative Adversarial 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)
- ImageNet: A large-scale hierarchical image database
Their papers
- Deep Generative Design: Integration of Topology Optimization and Generative Models (2019) — 410 citations