Mohamed Amine Ferrag
Computer Networks and Communications · 2017–2022
A researcher in the Science corpus: 7 papers; trusts 23 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 142 citations into it
- Artificial Intelligence — 79 citations into it
- Information Systems — 77 citations into it
- Electrical and Electronic Engineering — 46 citations into it
- Plant Science — 44 citations into it
- Computer Vision and Pattern Recognition — 37 citations into it
- Signal Processing — 31 citations into it
- Food Science — 15 citations into it
Whom Mohamed Amine Ferrag trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Oscar Novo
- Michael I. Jordan
- Geoffrey E. Hinton
- Jeffrey L. Elman
- Kaiming He
- Matthew D. Zeiler
- Christian Szegedy
- Gideon Creech
- Anna L. Buczak
- Yoshua Bengio
Who trusts Mohamed Amine Ferrag overall
Papers from Mohamed Amine Ferrag's perspective
Ordered by how strongly the researchers Mohamed Amine Ferrag trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Edge-IIoTset: A New Comprehensive Realistic Cyber Security Dataset of IoT and IIoT Applications for Centralized and Federated Learning (2022) — 906 citations
- Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies (2021) — 451 citations
- A Survey on Smart Agriculture: Development Modes, Technologies, and Security and Privacy Challenges (2021) — 323 citations
- Deep learning for cyber security intrusion detection: Approaches, datasets, and comparative study (2020) — 1,092 citations
- Security and Privacy for Green IoT-Based Agriculture: Review, Blockchain Solutions, and Challenges (2020) — 319 citations
- Blockchain Technologies for the Internet of Things: Research Issues and Challenges (2018) — 633 citations
- Security and Privacy in Fog Computing: Challenges (2017) — 484 citations