Philippe Lyonel Touko Mbouembe

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 90 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 18 citations into it
• Artificial Intelligence — 8 citations into it
• Plant Science — 7 citations into it
• Model Architectures — 6 citations into it

Whom Philippe Lyonel Touko Mbouembe trusts overall

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

1. Ross B. Girshick
2. Joseph Redmon
3. Kaiming He
4. Christian Szegedy
5. Tsung-Yi Lin
6. Alex Krizhevsky
7. Shaoqing Ren
8. Geoffrey E. Hinton
9. Sergey Ioffe
10. Ali Farhadi

Papers from Philippe Lyonel Touko Mbouembe's perspective

Ordered by how strongly the researchers Philippe Lyonel Touko Mbouembe 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
9. Long Short-Term Memory
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• YOLO-Tomato: A Robust Algorithm for Tomato Detection Based on YOLOv3 (2020) — 395 citations