Vahid Mirjalili
Computer Vision and Pattern Recognition · 2017–2019
A researcher in the Science corpus: 5 papers; trusts 115 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 39 citations into it
- Artificial Intelligence — 16 citations into it
- Signal Processing — 15 citations into it
- Cognitive Neuroscience — 11 citations into it
- Information Systems — 8 citations into it
- Optimization & Training — 5 citations into it
Whom Vahid Mirjalili trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Karl Ricanek Jr.
- Ziwei Liu
- Kaiming He
- Terence Sim
- Alex Krizhevsky
- Yoshua Bengio
- Antitza Dantcheva
- Yann LeCun
- Ross B. Girshick
Who trusts Vahid Mirjalili overall
Papers from Vahid Mirjalili's perspective
Ordered by how strongly the researchers Vahid Mirjalili 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- 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
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Semi-adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images (2017) — 117 citations
- Rank consistent ordinal regression for neural networks with application to age estimation (2019) — 370 citations
- FlowSAN: Privacy-Enhancing Semi-Adversarial Networks to Confound Arbitrary Face-Based Gender Classifiers (2019) — 50 citations
- ASD-DiagNet: A Hybrid Learning Approach for Detection of Autism Spectrum Disorder Using fMRI Data (2019) — 345 citations
- Python machine learning : machine learning and deep learning with Python, scikit-learn, and TensorFlow (2017) — 552 citations