Julio-Alejandro Romero-González

Computer Vision and Pattern Recognition · 2023

A researcher in the Science corpus: 2 papers; trusts 488 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 82 citations into it
• Artificial Intelligence — 58 citations into it
• Model Architectures — 14 citations into it
• Radiology, Nuclear Medicine and Imaging — 12 citations into it
• Optimization & Training — 7 citations into it

Whom Julio-Alejandro Romero-González trusts overall

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

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

Papers from Julio-Alejandro Romero-González's perspective

Ordered by how strongly the researchers Julio-Alejandro Romero-González 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Going deeper with convolutions
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

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