Silvia Cascianelli

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 2 papers; trusts 757 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 265 citations into it
• Artificial Intelligence — 175 citations into it
• Multimodal Learning — 165 citations into it
• Natural Language Processing — 72 citations into it
• Natural Language Generation — 37 citations into it
• Evaluation & Benchmarks — 34 citations into it
• Model Architectures — 26 citations into it
• Reinforcement Learning — 9 citations into it

Whom Silvia Cascianelli trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Kaiming He
4. Yoshua Bengio
5. Ilya Sutskever
6. Diederik P. Kingma
7. Karen Simonyan
8. Andrew Zisserman
9. Yann LeCun
10. Ross B. Girshick

Papers from Silvia Cascianelli's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• From Show to Tell: A Survey on Deep Learning-Based Image Captioning (2021) — 395 citations
• From Show to Tell: A Survey on Image Captioning (2021) — 58 citations