Angel Cruz-Roa

Computer Vision and Pattern Recognition · 2013–2017

A researcher in the Science corpus: 5 papers; trusts 12 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 50 citations into it; #16,622 of 21,575 by trust here, #6,146 by citations
• Artificial Intelligence — 44 citations into it; #26,824 of 35,345 by trust here, #5,970 by citations
• Representation & Self-Supervised Learning — 11 citations into it

Whom Angel Cruz-Roa trusts overall

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

1. Yoshua Bengio
2. Yann LeCun
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Ilya Sutskever
6. Koray Kavukcuoglu
7. Ronan Collobert
8. Quoc V. Le
9. Pascal Vincent
10. Aaron C. Courville

Who trusts Angel Cruz-Roa overall

1. Anant Madabhushi
2. Andrew Janowczyk
3. Jun Xu
4. Devinder Kumar
5. Chetan L. Srinidhi
6. Geert J. S. Litjens
7. Hao Chen
8. J. A. van der Laak
9. Neslihan Bayramoglu
10. Bruno Korbar

Papers from Angel Cruz-Roa's perspective

Ordered by how strongly the researchers Angel Cruz-Roa trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks (2014) — 632 citations
• A Deep Learning Architecture for Image Representation, Visual Interpretability and Automated Basal-Cell Carcinoma Cancer Detection (2013) — 389 citations
• Assessment of algorithms for mitosis detection in breast cancer histopathology images (2014) — 464 citations
• Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent (2017) — 479 citations
• Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features (2014) — 334 citations