Shin-Ming Cheng

Computer Vision and Pattern Recognition · 2012–2018

A researcher in the Science corpus: 2 papers; 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
• Computer Networks and Communications — 6 citations into it

Whom Shin-Ming Cheng trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Réka Albert

Papers from Shin-Ming Cheng's perspective

Ordered by how strongly the researchers Shin-Ming Cheng trusts endorse each paper. Same corpus, a different order for every researcher.

1. Gradient-based learning applied to document recognition
2. Learning Multiple Layers of Features from Tiny Images
3. ImageNet Large Scale Visual Recognition Challenge
4. Intriguing properties of neural networks
5. Rethinking the Inception Architecture for Computer Vision
6. Explaining and Harnessing Adversarial Examples
7. Towards Evaluating the Robustness of Neural Networks
8. TensorFlow: A system for large-scale machine learning
9. Practical Black-Box Attacks against Machine Learning
10. Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

Their papers

• AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks (2018) — 452 citations
• Smart attacks in smart grid communication networks (2012) — 196 citations