Mohamed Adel Serhani

Artificial Intelligence · 2016–2022

A researcher in the Science corpus: 4 papers; trusts 37 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 88 citations into it
• Electrical and Electronic Engineering — 37 citations into it
• Computer Networks and Communications — 30 citations into it
• Computer Vision and Pattern Recognition — 28 citations into it
• Federated & Distributed Learning — 23 citations into it
• Information Systems — 11 citations into it
• Management Science and Operations Research — 11 citations into it
• Optimization & Training — 11 citations into it

Whom Mohamed Adel Serhani trusts overall

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

1. J. Urgen Schmidhuber
2. Kaiming He
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Sebastian U. Stich
7. H. Brendan McMahan
8. Yann LeCun
9. Ilya Sutskever
10. Diederik P. Kingma

Papers from Mohamed Adel Serhani's perspective

Ordered by how strongly the researchers Mohamed Adel Serhani 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Learning Multiple Layers of Features from Tiny Images
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Attention is All you Need (Neural Information Processing Systems)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches † (2018) — 845 citations
• Federated Learning in Edge Computing: A Systematic Survey (2022) — 303 citations
• ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges (2020) — 312 citations
• Big Data Quality: A Quality Dimensions Evaluation (2016) — 81 citations