Girish Kulkarni
Computer Vision and Pattern Recognition · with Berg · 2011–2013
A researcher in the Science corpus: 5 papers; trusts 404 researchers and is trusted by 3,242 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 86 citations into it; #634 of 21,575 by trust here, #1,250 by citations
- Natural Language Processing — 28 citations into it; #507 of 5,688 by trust here, #752 by citations
- Artificial Intelligence — 27 citations into it; #5,887 of 35,345 by trust here, #3,757 by citations
- Multimodal Learning — 19 citations into it; #21 of 1,211 by trust here, #83 by citations
- Evaluation & Benchmarks — 17 citations into it
- Information Extraction — 9 citations into it
- Signal Processing — 6 citations into it
Whom Girish Kulkarni trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Antonio Torralba
- Jia Deng
- Geoffrey E. Hinton
- Ali Farhadi
- Abhinav Kumar Gupta
- Andrew Zisserman
- Alex Krizhevsky
- Kaiming He
- Ross B. Girshick
- Vladimir Kolmogorov
Who trusts Girish Kulkarni overall
- Zhe Gan
- Andrej Karpathy
- Xinlei Chen
- Devi Parikh
- C. Lawrence Zitnick
- Marcus Rohrbach
- Li Fei-Fei
- Qi Wu
- Ruslan Salakhutdinov
- Ryan Kiros
Papers from Girish Kulkarni's perspective
Ordered by how strongly the researchers Girish Kulkarni trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Im2Text: Describing Images Using 1 Million Captioned Photographs (2011) — 1,594 citations
- BabyTalk: Understanding and Generating Simple Image Descriptions (2013) — 1,067 citations
- Baby talk: Understanding and generating simple image descriptions (2011) — 190 citations
- Baby Talk: Understanding and Generating Image Descriptions (2011)
- Composing Simple Image Descriptions using Web-scale N-grams (2011) — 416 citations