Ala Al-Fuqaha
Artificial Intelligence · 2015–2023
A researcher in the Science corpus: 15 papers; trusts 413 researchers and is trusted by 23 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 389 citations into it; #20,703 of 35,345 by trust here, #8,999 by citations
- Computer Networks and Communications — 240 citations into it; #1,526 of 9,886 by trust here, #215 by citations
- Computer Vision and Pattern Recognition — 182 citations into it
- Electrical and Electronic Engineering — 142 citations into it; #14,294 of 16,539 by trust here, #6,291 by citations
- Safety, Robustness & Interpretability — 89 citations into it
- Signal Processing — 73 citations into it
- Information Systems — 69 citations into it
- Aerospace Engineering — 60 citations into it
Whom Ala Al-Fuqaha trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Diederik P. Kingma
- Yann LeCun
- Ilya Sutskever
- Kaiming He
- J. Urgen Schmidhuber
- L. Eon Bottou
- Alex Graves
Who trusts Ala Al-Fuqaha overall
- M. Mohammadi
- Fatima Hussain
- Shree Krishna Sharma
- Sharief M. A. Oteafy
- Dinh C. Nguyen
- Wei Yu
- Abdullah Alsaedi
- Mingzhe Chen
- Abderahman Rejeb
- Ayca Kirimtat
Papers from Ala Al-Fuqaha's perspective
Ordered by how strongly the researchers Ala Al-Fuqaha 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges (2018) — 1,931 citations
- Semisupervised Deep Reinforcement Learning in Support of IoT and Smart City Services (2018) — 376 citations
- Smart Cities: A Survey on Data Management, Security, and Enabling Technologies (2017) — 515 citations
- Privacy-preserving artificial intelligence in healthcare: Techniques and applications (2023) — 415 citations
- Intelligent Building Control Systems for Thermal Comfort and Energy-Efficiency: A Systematic Review of Artificial Intelligence-Assisted Techniques (2021) — 367 citations
- Explainable, trustworthy, and ethical machine learning for healthcare: A survey (2021) — 320 citations
- Secure and Robust Machine Learning for Healthcare: A Survey (2020) — 471 citations
- Exploiting Unlabeled Data in Smart Cities using Federated Learning (2020) — 20 citations
- Blockchain for AI: Review and Open Research Challenges (2019) — 775 citations
- Enabling Cognitive Smart Cities Using Big Data and Machine Learning: Approaches and Challenges (2018) — 306 citations
- Online Auction of Cloud Resources in Support of the Internet of Things (2017) — 30 citations
- Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges (2017) — 433 citations
- Deep Learning for IoT Big Data and Streaming Analytics: A Survey (2017) — 1,196 citations
- Toward better horizontal integration among IoT services (2015) — 207 citations
- Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications (2015) — 7,425 citations