Kemi Victoria Dada

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 Kemi Victoria Dada trusts overall

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

1. Simon S. Haykin
2. Yoshua Bengio

Papers from Kemi Victoria Dada's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
4. Gradient-based learning applied to document recognition
5. Learning Deep Architectures for AI
6. Deep Learning
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Long Short-Term Memory
9. A unified architecture for natural language processing: deep neural networks with multitask learning
10. Going deeper with convolutions

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