Essam H. Houssein
Artificial Intelligence · 2018–2022
A researcher in the Science corpus: 8 papers; trusts 43 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 243 citations into it; #20,666 of 35,345 by trust here, #10,430 by citations
- Computational Theory and Mathematics — 140 citations into it; #10,586 of 12,182 by trust here, #2,251 by citations
- Computer Vision and Pattern Recognition — 51 citations into it
- Cognitive Neuroscience — 29 citations into it
- Experimental and Cognitive Psychology — 23 citations into it
- Signal Processing — 14 citations into it
- Model Architectures — 12 citations into it
- Molecular Biology — 12 citations into it
Whom Essam H. Houssein trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Seyedali Mirjalili
- Sepp Hochreiter
- Abdulhamit Subasi
- Carlos Artemio Coello Coello
- Juha Reunanen
- Yoshua Bengio
- Aapo Hyvärinen
- R. Eberhart
- Ron Kohavi
- Geoffrey E. Hinton
Who trusts Essam H. Houssein overall
- M. Ahsan
- Meghavi Rana
- Fatma A. Hashim
- Zahed Siddique
- Megha Bhushan
- Mohammad-Hossein Nadimi-Shahraki
- Pavel Trojovský
- Mohammed Azmi Al-Betar
Papers from Essam H. Houssein's perspective
Ordered by how strongly the researchers Essam H. Houssein trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Going deeper with convolutions
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems (2020) — 968 citations
- Henry gas solubility optimization: A novel physics-based algorithm (2019) — 923 citations
- Lévy flight distribution: A new metaheuristic algorithm for solving engineering optimization problems (2020) — 427 citations
- Honey Badger Algorithm: New metaheuristic algorithm for solving optimization problems (2022) — 1,108 citations
- Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review (2022) — 357 citations
- Deep and machine learning techniques for medical imaging-based breast cancer: A comprehensive review (2021) — 347 citations
- Major Advances in Particle Swarm Optimization: Theory, Analysis, and Application (2021) — 412 citations
- Improved grasshopper optimization algorithm using opposition-based learning (2018) — 321 citations