Tal Arbel

Computer Vision and Pattern Recognition · 2011–2023

A researcher in the Science corpus: 8 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 138 citations into it
• Artificial Intelligence — 79 citations into it
• Radiology, Nuclear Medicine and Imaging — 71 citations into it
• Safety, Robustness & Interpretability — 10 citations into it

Whom Tal Arbel trusts overall

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

1. Geoffrey E. Hinton
2. Matthew D. Zeiler
3. Yarin Gal
4. Christian Szegedy
5. Daniel Cremers
6. Alex Kendall
7. Alex Krizhevsky
8. Yann LeCun
9. Yoshua Bengio
10. L. V. D. van der Maaten

Papers from Tal Arbel's perspective

Ordered by how strongly the researchers Tal Arbel 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. ImageNet: A large-scale hierarchical image database
4. Going deeper with convolutions
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. ImageNet Large Scale Visual Recognition Challenge
8. Attention is All you Need (Neural Information Processing Systems)
9. Long Short-Term Memory
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) (2015) — 6,325 citations
• Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation (2023) — 975 citations
• Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge (2011) — 492 citations
• Why rankings of biomedical image analysis competitions should be interpreted with care (2018) — 393 citations
• Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support (2017) — 432 citations
• Metrics Reloaded: Recommendations for image analysis validation (2022) — 479 citations
• Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge (2018) — 2,033 citations
• Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation (2018) — 510 citations