Kimmel, Ron

A Gromov-Hausdorff Framework with Diffusion Geometry for Topologically-Robust Non-rigid Shape Matching

Bronstein, A. M., Bronstein, M. M., Kimmel, R., Mahmoudi, M., & Sapiro, G. (2010) · International Journal of Computer Vision

3D Shape Modeling and AnalysisTopological and Geometric Data Analysis

Cited by 267

Deep learning-based image analysis predicts PD-L1 status from H&E-stained histopathology images in breast cancer

Shamai, G., Livne, A., Polónia, A., Sabo, E., Cretu, A., Bar-Sela, G., & Kimmel, R. (2022) · Nature Communications

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 193

A Deep Learning Perspective on the Origin of Facial Expressions

Breuer, R., & Kimmel, R. (2017) · arXiv

Emotion and Mood RecognitionFace recognition and analysis

Cited by 92

FuseCap: Leveraging Large Language Models for Enriched Fused Image Captions

Rotstein, N., Bensaïd, D., Brody, S., Ganz, R., & Kimmel, R. (2024) · 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

Multimodal Machine Learning ApplicationsImage Retrieval and Classification Techniques

Cited by 66

Pathways on the Image Manifold: Image Editing via Video Generation

Rotstein, N., Yona, G., Silver, D., Velich, R., Bensaïd, D., & Kimmel, R. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisDigital Media Forensic Detection

Cited by 5

Deep learning on histopathological images to predict breast cancer recurrence risk and chemotherapy benefit

Shamai, G., Cohen, S., Binenbaum, Y., Sabo, E., Cretu, A., Mayer, C., Barshack, I., Goldman, T., Bar-Sela, G., Polónia, A., et al. (2025) · medRxiv

AI in cancer detectionBreast Cancer Treatment Studies

Cited by 3