Követés
Srishti Gautam
Cím
Hivatkozott rá
Hivatkozott rá
Év
Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels
S Hansen, S Gautam, R Jenssen, M Kampffmeyer
Medical Image Analysis 78, 102385, 2022
1042022
This looks more like that: Enhancing self-explaining models by prototypical relevance propagation
S Gautam, MMC Höhne, S Hansen, R Jenssen, M Kampffmeyer
Pattern Recognition 136, 109172, 2023
482023
Protovae: A trustworthy self-explainable prototypical variational model
S Gautam, A Boubekki, S Hansen, S Salahuddin, R Jenssen, M Höhne, ...
Advances in Neural Information Processing Systems 35, 17940-17952, 2022
462022
Considerations for a PAP smear image analysis system with CNN features
S Gautam, N Jith, AK Sao, A Bhavsar, A Natarajan
arXiv preprint arXiv:1806.09025, 2018
422018
CNN based segmentation of nuclei in PAP-smear images with selective pre-processing
S Gautam, A Bhavsar, AK Sao, KK Harinarayan
Medical Imaging 2018: Digital Pathology 10581, 246-254, 2018
412018
DeepCerv: Deep neural network for segmentation free robust cervical cell classification
OU Nirmal Jith, KK Harinarayanan, S Gautam, A Bhavsar, AK Sao
Computational Pathology and Ophthalmic Medical Image Analysis: First …, 2018
342018
ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement
S Hansen, S Gautam, SA Salahuddin, M Kampffmeyer, R Jenssen
Medical Image Analysis 89, 102870, 2023
172023
Demonstrating the risk of imbalanced datasets in chest x-ray image-based diagnostics by prototypical relevance propagation
S Gautam, MMC Höhne, S Hansen, R Jenssen, M Kampffmeyer
2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 1-5, 2022
112022
Investigating the fairness of large language models for predictions on tabular data
Y Liu, S Gautam, J Ma, H Lakkaraju
arXiv preprint arXiv:2310.14607, 2023
102023
Confronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classifications
Y Liu, S Gautam, J Ma, H Lakkaraju
Proceedings of the 2024 Conference of the North American Chapter of the …, 2024
92024
Unsupervised segmentation of cervical cell nuclei via adaptive clustering
S Gautam, K Gupta, A Bhavsar, AK Sao
Medical Image Understanding and Analysis: 21st Annual Conference, MIUA 2017 …, 2017
92017
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S Gautam, A Bhavsar, AK Sao
CNN based segmentation of nuclei in PAP-smear images with selective …, 2018
62018
Prototypical Self-Explainable Models Without Re-training
S Gautam, A Boubekki, M Höhne, MC Kampffmeyer
arXiv preprint arXiv:2312.07822, 2023
32023
A self-guided anomaly detection-inspired few-shot segmentation network
SA Salahuddin, S Hansen, S Gautam, M Kampffmeyer, R Jenssen
CEUR Workshop Proceedings, 2022
32022
MicroGAN: size-invariant learning of GAN for super-resolution of microscopic images
S Gautam, DK Pradhan, PC Chhipa, S Nakajima
MICCAI 2019 Computational Pathology Workshop COMPAY, 2019
22019
A self-guided anomaly detection-inspired few-shot segmentation network
R Jenssen, S Hansen, S Gautam, M Kampffmeyer
12022
Segmentation and Classification of Nuclei in PAP-smear Images for Automated Cervical Cancer Screening
S Gautam
12017
Towards Interpretable, Trustworthy and Reliable AI
S Gautam
UiT Norges arktiske universitet, 2024
2024
This looks More Like that: Enhancing Self-Explaining Models by prototypical relevance propagation: This Looks More Like That
S Gautam, MMC Höhne, S Hansen, R Jenssen, M Kampffmeyer
Amsterdam: Elsevier, 2022
2022
NUCLEUS-BASED CERVICAL CELL CLASSIFICATION IN PAP SMEAR IMAGES USING DECISION-TREE BASED APPROACH
K Gupta, S Gautam, AK Sao, A Bhavsar
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Cikkek 1–20