S. Chang
Computer Vision and Pattern Recognition · with Park · 2018
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 — 10 citations into it
Whom S. Chang trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Karen Simonyan (in Computer Vision and Pattern Recognition)
- Andrew Zisserman (in Computer Vision and Pattern Recognition)
- Alex Krizhevsky (in Computer Vision and Pattern Recognition)
- Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)
Papers from S. Chang's perspective
Ordered by how strongly the researchers S. Chang trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Dropout: a simple way to prevent neural networks from overfitting
- Dermatologist-level classification of skin cancer with deep neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
- Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer