Aneesh Rangnekar

According to our database, Aneesh Rangnekar authored at least 23 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Co-distilled attention guided masked image modeling with noisy teacher for self-supervised learning on medical images.

Jue Jiang, Aneesh Rangnekar, Harini Veeraraghavan

CoRR, April, 2026

MHub.ai: A Simple, Standardized, and Reproducible Platform for AI Models in Medical Imaging.

Leonard Nürnberg, Dennis Bontempi, Suraj Pai, Curtis Lisle, Steven D. Pieper, Ron Kikinis, Sil van de Leemput, Rahul Soni, Gowtham Murugesan, Cosmin Ciausu, Miriam Groeneveld, Felix J. Dorfner, Jue Jiang, Aneesh Rangnekar, Harini Veeraraghavan, Joeran S. Bosma, Keno K. Bressem, Raymond H. Mak, Andrey Fedorov, Hugo J. W. L. Aerts

CoRR, January, 2026

brat : Aligned Multi-View Embeddings for Brain MRI Analysis.

Maxime Kayser, Maksim Gridnev, Wanting Wang, Max Bain, Aneesh Rangnekar, Avijit Chatterjee, Aleksandr Petrov, Harini Veeraraghavan, Nathaniel C. Swinburne

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2026

Dual Cross-Attention Siamese Transformer for Rectal Tumor Regrowth Assessment in Watch-and-Wait Endoscopy.

Jorge Tapias Gomez, Despoina Kanata, Aneesh Rangnekar, Christina Lee, Joshua Jesse Smith, Julio Garcia-Aguilar, Harini Veeraraghavan

Proceedings of the 23rd IEEE International Symposium on Biomedical Imaging, 2026

2025

Tumor-anchored deep feature random forests for out-of-distribution detection in lung cancer segmentation.

Aneesh Rangnekar, Harini Veeraraghavan

CoRR, December, 2025

Random forest-based out-of-distribution detection for robust lung cancer segmentation.

Aneesh Rangnekar, Harini Veeraraghavan

CoRR, August, 2025

Pretrained hybrid transformer for generalizable cardiac substructures segmentation from contrast and non-contrast CTs in lung and breast cancers.

Aneesh Rangnekar, Nikhil Mankuzhy, Jonas Willmann, Chloe Min Seo Choi, Abraham J. Wu, Maria Thor, Andreas Rimner, Harini Veeraraghavan

CoRR, May, 2025

2024

Self-supervised learning improves robustness of deep learning lung tumor segmentation to CT imaging differences.

Jue Jiang, Aneesh Rangnekar, Harini Veeraraghavan

CoRR, 2024

Deep learning classifier of locally advanced rectal cancer treatment response from endoscopy images.

Jorge Tapias Gomez, Aneesh Rangnekar, Hannah Williams, Hannah Thompson, Julio Garcia-Aguilar, Joshua Jesse Smith, Harini Veeraraghavan

CoRR, 2024

Trustworthiness of Pretrained Transformers for Lung Cancer Segmentation.

Aneesh Rangnekar, Nishant Nadkarni, Jue Jiang, Harini Veeraraghavan

CoRR, 2024

2023

Semantic Segmentation with Active Semi-Supervised Learning.

Aneesh Rangnekar, Christopher Kanan, Matthew J. Hoffman

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

3D Swin Transformer for Partial Medical Auto Segmentation.

Aneesh Rangnekar, Jue Jiang, Harini Veeraraghavan

Proceedings of the Fast, Low-resource, and Accurate Organ and Pan-cancer Segmentation in Abdomen CT, 2023

2022

SpecAL: Towards Active Learning for Semantic Segmentation of Hyperspectral Imagery.

Aneesh Rangnekar, Emmett J. Ientilucci, Christopher Kanan, Matthew J. Hoffman

Proceedings of the Dynamic Data Driven Applications Systems - 4th International Conference, 2022

Semi-Supervised Hyperspectral Object Detection Challenge Results - PBVS 2022.

Aneesh Rangnekar, Zachary Mulhollan, Anthony Vodacek, Matthew J. Hoffman, Ángel D. Sappa, Erik Blasch, Jun Yu, Liwen Zhang, Shenshen Du, Hao Chang, Keda Lu, Zhong Zhang, Fang Gao, Ye Yu, Feng Shuang, Lei Wang, Qiang Ling, Pranjay Shyam, Kuk-Jin Yoon, Kyung-Soo Kim

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Semantic Segmentation with Active Semi-Supervised Representation Learning.

Aneesh Rangnekar, Christopher Kanan, Matthew J. Hoffman

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2020

AeroRIT: A New Scene for Hyperspectral Image Analysis.

Aneesh Rangnekar, Nilay Mokashi, Emmett J. Ientilucci, Christopher Kanan, Matthew J. Hoffman

IEEE Trans. Geosci. Remote. Sens., 2020

Fine-Tuning for One-Look Regression Vehicle Counting in Low-Shot Aerial Datasets.

Aneesh Rangnekar, Yi Yao, Matthew J. Hoffman, Ajay Divakaran

Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

Uncertainty Estimation for Semantic Segmentation of Hyperspectral Imagery.

Aneesh Rangnekar, Emmett J. Ientilucci, Christopher Kanan, Matthew J. Hoffman

Proceedings of the Dynamic Data Driven Applications Systems, 2020

Occlusion Detection for Dynamic Adaptation.

Zachary Mulhollan, Aneesh Rangnekar, Anthony Vodacek, Matthew J. Hoffman

Proceedings of the Dynamic Data Driven Applications Systems, 2020

Calibrated Vehicle Paint Signatures for Simulating Hyperspectral Imagery.

Zachary Mulhollan, Aneesh Rangnekar, Timothy D. Bauch, Matthew J. Hoffman, Anthony Vodacek

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Tracking in Aerial Hyperspectral Videos Using Deep Kernelized Correlation Filters.

Burak Uzkent, Aneesh Rangnekar, Matthew J. Hoffman

IEEE Trans. Geosci. Remote. Sens., 2019

2017

Aerial Spectral Super-Resolution using Conditional Adversarial Networks.

Aneesh Rangnekar, Nilay Mokashi, Emmett J. Ientilucci, Christopher Kanan, Matthew J. Hoffman

CoRR, 2017

Aerial Vehicle Tracking by Adaptive Fusion of Hyperspectral Likelihood Maps.

Burak Uzkent, Aneesh Rangnekar, Matthew J. Hoffman

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017