Humaira Arshad

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 42 citations into it
• Electrical and Electronic Engineering — 11 citations into it
• Management Science and Operations Research — 7 citations into it

Whom Humaira Arshad trusts

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

1. Weizhong Yan (in Artificial Intelligence)
2. Simon S. Haykin (in Artificial Intelligence)
3. Soteris A. Kalogirou (in Artificial Intelligence)
4. Yoshua Bengio (in Artificial Intelligence)

Papers from Humaira Arshad's perspective

Ordered by how strongly the researchers Humaira Arshad trusts endorse each paper. Same corpus, a different order for every researcher.

1. Learning Deep Architectures for AI
2. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
3. Deep Learning
4. A unified architecture for natural language processing: deep neural networks with multitask learning
5. ImageNet classification with deep convolutional neural networks
6. Convolutional networks for images, speech, and time series
7. Domain-Adversarial Training of Neural Networks
8. Autoencoding beyond pixels using a learned similarity metric
9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
10. Gradient-based learning applied to document recognition

Their papers

• Comprehensive Review of Artificial Neural Network Applications to Pattern Recognition (2019) — 562 citations
• State-of-the-art in artificial neural network applications: A survey (2018) — 2,641 citations