Ee-Chien Chang
Artificial Intelligence · 2001–2019
A researcher in the Science corpus: 9 papers; trusts 242 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 157 citations into it; #26,673 of 35,345 by trust here, #15,236 by citations
- Computer Vision and Pattern Recognition — 67 citations into it; #9,957 of 21,575 by trust here, #12,172 by citations
- Safety, Robustness & Interpretability — 62 citations into it; #1,728 of 2,251 by trust here, #1,496 by citations
- Information Systems — 58 citations into it
- Computer Networks and Communications — 43 citations into it; #7,183 of 9,886 by trust here, #4,594 by citations
- Privacy & Security — 38 citations into it
- Signal Processing — 38 citations into it; #5,612 of 7,572 by trust here, #3,673 by citations
- Computational Theory and Mathematics — 12 citations into it
Whom Ee-Chien Chang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Ian J. Goodfellow
- Christian Szegedy
- Alex Krizhevsky
- Yann LeCun
- Matthew D. Zeiler
- Yoshua Bengio
- Kaiming He
- Ilya Sutskever
- Karen Simonyan
Who trusts Ee-Chien Chang overall
Papers from Ee-Chien Chang's perspective
Ordered by how strongly the researchers Ee-Chien Chang 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
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Detecting Digital Image Forgeries by Measuring Inconsistencies of Blocking Artifact (2007) — 305 citations
- A fast direct Fourier-based algorithm for subpixel registration of images (2001) — 385 citations
- Evading Classifiers by Morphing in the Dark (2017) — 126 citations
- Neural Network Inversion in Adversarial Setting via Background Knowledge Alignment (2019) — 263 citations
- Privacy-Preserving Computation with Trusted Computing via Scramble-then-Compute (2017) — 25 citations
- Adversarial Neural Network Inversion via Auxiliary Knowledge Alignment (2019) — 71 citations
- Towards Scaling Blockchain Systems via Sharding (2018) — 546 citations
- M2R: Enabling Stronger Privacy in MapReduce Computation (2015) — 131 citations
- Security of Public Watermarking Schemes for Binary Sequences (2002) — 6 citations