Sinisa Segvic

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 424 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 79 citations into it; #9,405 of 21,575 by trust here, #12,419 by citations
• Artificial Intelligence — 51 citations into it
• Generative Models — 40 citations into it
• Model Architectures — 19 citations into it
• Probabilistic & Bayesian Methods — 12 citations into it
• Optimization & Training — 10 citations into it
• Signal Processing — 10 citations into it
• Statistical and Nonlinear Physics — 8 citations into it

Whom Sinisa Segvic trusts overall

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

1. Diederik P. Kingma
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Kaiming He
5. Yoshua Bengio
6. Yann LeCun
7. Ross B. Girshick
8. Ilya Sutskever
9. Christian Szegedy
10. Radford M. Neal

Who trusts Sinisa Segvic overall

1. Dan Friedman

Papers from Sinisa Segvic's perspective

Ordered by how strongly the researchers Sinisa Segvic 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• In Defense of Pre-Trained ImageNet Architectures for Real-Time Semantic Segmentation of Road-Driving Images (2019) — 393 citations
• Densely connected normalizing flows (2021) — 66 citations