Toby P. Breckon

Computer Vision and Pattern Recognition · 2011–2021

A researcher in the Science corpus: 7 papers; trusts 1,301 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 166 citations into it; #6,306 of 21,575 by trust here, #6,146 by citations
• Artificial Intelligence — 89 citations into it; #10,366 of 35,345 by trust here, #10,798 by citations
• Generative Models — 76 citations into it
• Model Architectures — 22 citations into it
• Optimization & Training — 19 citations into it
• Representation & Self-Supervised Learning — 17 citations into it
• Computer Networks and Communications — 16 citations into it
• Media Technology — 15 citations into it; #2,427 of 3,621 by trust here, #2,389 by citations

Whom Toby P. Breckon trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ross B. Girshick
5. Diederik P. Kingma
6. Karen Simonyan
7. Yoshua Bengio
8. Yann LeCun
9. Ilya Sutskever
10. Andrew Zisserman

Who trusts Toby P. Breckon overall

1. Vitjan Zavrtanik
2. Garrett Wilson
3. Samet Akcay
4. Yongcheng Jing
5. Hanqiu Deng
6. Erik A. Daxberger
7. Shu Kong
8. Trong-Nguyen Nguyen
9. Matej Kristan
10. Diane Joyce Cook

Papers from Toby P. Breckon's perspective

Ordered by how strongly the researchers Toby P. Breckon 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Models (2021) — 220 citations
• GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training (2018) — 1,738 citations
• Real-Time Monocular Depth Estimation Using Synthetic Data with Domain Adaptation via Image Style Transfer (2018) — 294 citations
• Using Deep Convolutional Neural Network Architectures for Object Classification and Detection Within X-Ray Baggage Security Imagery (2018) — 329 citations
• An evaluation of region based object detection strategies within X-ray baggage security imagery (2017) — 84 citations
• Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection (2019) — 461 citations
• Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab (2011) — 686 citations