Yakoub Bazi

Computer Vision and Pattern Recognition · 2005–2021

A researcher in the Science corpus: 9 papers; trusts 308 researchers and is trusted by 42 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 107 citations into it; #6,587 of 21,575 by trust here, #9,187 by citations
• Artificial Intelligence — 63 citations into it; #31,850 of 35,345 by trust here, #33,294 by citations
• Media Technology — 62 citations into it; #354 of 3,621 by trust here, #633 by citations
• Atmospheric Science — 20 citations into it; #520 of 4,804 by trust here, #2,621 by citations
• Cardiology and Cardiovascular Medicine — 14 citations into it; #169 of 906 by trust here, #358 by citations
• Cognitive Neuroscience — 14 citations into it; #4,233 of 10,852 by trust here, #5,043 by citations
• Optimization & Training — 14 citations into it
• Ecology — 12 citations into it

Whom Yakoub Bazi trusts overall

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

1. Geoffrey E. Hinton
2. Lorenzo Bruzzone
3. Yuhai Wu
4. Alex Krizhevsky
5. Yoshua Bengio
6. M. Stone
7. Kaiming He
8. Yi Yang
9. J. Urgen Schmidhuber
10. Ilya Sutskever

Who trusts Yakoub Bazi overall

1. Abdulhamit Subasi
2. Pedram Ghamisi
3. Maoguo Gong
4. Farid Melgani
5. Gabriele Moser
6. Jon Atli Benediktsson
7. Ajay Mathur
8. Francesca Bovolo
9. Victor Francisco Rodriguez-Galiano
10. Aaron E. Maxwell

Papers from Yakoub Bazi's perspective

Ordered by how strongly the researchers Yakoub Bazi 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. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Land-Use Classification With Compressive Sensing Multifeature Fusion (2015) — 75 citations
• Classification of Remote Sensing Images Using EfficientNet-B3 CNN Model With Attention (2021) — 298 citations
• Vision Transformers for Remote Sensing Image Classification (2021) — 575 citations
• Continual Learning Approach for Remote Sensing Scene Classification (2020) — 20 citations
• Deep learning approach for active classification of electrocardiogram signals (2016) — 601 citations
• Using convolutional features and a sparse autoencoder for land-use scene classification (2016) — 153 citations
• Classification of Electrocardiogram Signals With Support Vector Machines and Particle Swarm Optimization (2008) — 506 citations
• Toward an Optimal SVM Classification System for Hyperspectral Remote Sensing Images (2006) — 456 citations
• An unsupervised approach based on the generalized Gaussian model to automatic change detection in multitemporal SAR images (2005) — 751 citations