Erhu Zhang

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Erhu Zhang trusts

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

  1. Yedid Hoshen (in Artificial Intelligence)
  2. Niv Cohen (in Artificial Intelligence)

Papers from Erhu Zhang's perspective

Ordered by how strongly the researchers Erhu Zhang trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
  2. MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection (Computer Vision and Pattern Recognition)
  3. GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training (Asian Conference on Computer Vision)
  4. Cascade R-CNN: Delving Into High Quality Object Detection
  5. Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders (VISIGRAPP)
  6. f‐AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks (Medical Image Anal.)
  7. Sub-Image Anomaly Detection with Deep Pyramid Correspondences (arXiv.org)
  8. Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction
  9. Road Crack Detection Using Deep Convolutional Neural Network and Adaptive Thresholding (2019 IEEE Intelligent Vehicles Symposium (IV))
  10. PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization (ICPR Workshops)

Their papers