Ferda Ofli

Computer Vision and Pattern Recognition · 2012–2018

A researcher in the Science corpus: 8 papers; trusts 343 researchers and is trusted by 36 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 83 citations into it; #4,571 of 21,575 by trust here, #3,489 by citations
• Artificial Intelligence — 44 citations into it; #33,697 of 35,345 by trust here, #11,327 by citations
• Biomedical Engineering — 15 citations into it; #2,011 of 10,734 by trust here, #2,377 by citations
• Natural Language Processing — 15 citations into it
• Representation & Self-Supervised Learning — 14 citations into it
• Multimodal Learning — 12 citations into it; #422 of 1,211 by trust here, #547 by citations
• Communication — 7 citations into it
• Human-Computer Interaction — 7 citations into it; #320 of 2,253 by trust here, #187 by citations

Whom Ferda Ofli trusts overall

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

1. Geoffrey E. Hinton
2. Ivan Laptev
3. Alex Krizhevsky
4. Graham W. Taylor
5. Kaiming He
6. Karen Simonyan
7. Ilya Sutskever
8. Wanqing Li
9. Yoshua Bengio
10. Marcin Marszalek

Who trusts Ferda Ofli overall

1. Yong Du
2. Suraj Vantigodi
3. Liliana Lo Presti
4. Cheng Chen
5. Roozbeh Jafari
6. Ioannis Kapsouras
7. Earnest Paul Ijjina
8. Matteo Munaro
9. Jun Liu
10. Fei Han

Papers from Ferda Ofli's perspective

Ordered by how strongly the researchers Ferda Ofli 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Berkeley MHAD: A comprehensive Multimodal Human Action Database (2013) — 515 citations
• Learning Cross-Modal Embeddings for Cooking Recipes and Food Images (2017) — 316 citations
• Bio-inspired Dynamic 3D Discriminative Skeletal Features for Human Action Recognition (2013) — 166 citations
• Sequence of the Most Informative Joints (SMIJ): A new representation for human skeletal action recognition (2012) — 404 citations
• Recipe1M: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images (2018) — 386 citations
• CrisisMMD: Multimodal Twitter Datasets from Natural Disasters (2018) — 432 citations
• Face-to-BMI: Using Computer Vision to Infer Body Mass Index on Social Media (2017) — 78 citations
• Accuracy and robustness of Kinect pose estimation in the context of coaching of elderly population (2012) — 374 citations