Diana-Margarita Córdova-Esparza

Computer Vision and Pattern Recognition · 2023

A researcher in the Science corpus: 3 papers; trusts 1,002 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 140 citations into it; #15,096 of 21,575 by trust here, #20,756 by citations
• Artificial Intelligence — 92 citations into it
• Model Architectures — 23 citations into it
• Radiology, Nuclear Medicine and Imaging — 21 citations into it; #1,718 of 3,265 by trust here, #3,230 by citations
• Evaluation & Benchmarks — 12 citations into it
• Optimization & Training — 12 citations into it
• Aerospace Engineering — 11 citations into it
• Efficiency & Compression — 6 citations into it

Whom Diana-Margarita Córdova-Esparza trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Christian Szegedy
4. Tsung-Yi Lin
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Shaoqing Ren
8. Sergey Ioffe
9. Yoshua Bengio
10. Yann LeCun

Who trusts Diana-Margarita Córdova-Esparza overall

1. Dillon Reis

Papers from Diana-Margarita Córdova-Esparza's perspective

Ordered by how strongly the researchers Diana-Margarita Córdova-Esparza trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
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

• A comprehensive survey of loss functions and metrics in deep learning (2023) — 304 citations
• A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS (2023) — 2,722 citations
• A Comprehensive Review of YOLO: From YOLOv1 to YOLOv8 and Beyond (2023) — 524 citations