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Santosh Sanjeev
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2020 – today
- 2024
- [c5]Santosh Sanjeev
, Nuren Zhaksylyk, Ibrahim Almakky, Anees Ur Rehman Hashmi, Mohammad Areeb Qazi
FissionFusion: Fast Geometric Generation and Hierarchical Souping for Medical Image Analysis. MICCAI (12) 2024: 131-141 - [c4]Santosh Sanjeev
TiBiX: Leveraging Temporal Information for Bidirectional X-Ray and Report Generation. DGM4MICCAI@MICCAI 2024: 169-179 - [c3]Mohammad Areeb Qazi
DynaMMo: Dynamic Model Merging for Efficient Class Incremental Learning for Medical Images. MIUA (1) 2024: 245-257 - [i8]Anees Ur Rehman Hashmi, Ibrahim Almakky, Mohammad Areeb Qazi, Santosh Sanjeev, Vijay Ram Papineni, Dwarikanath Mahapatra, Mohammad Yaqub:
XReal: Realistic Anatomy and Pathology-Aware X-ray Generation via Controllable Diffusion Model. CoRR abs/2403.09240 (2024) - [i7]Ibrahim Almakky, Santosh Sanjeev, Anees Ur Rehman Hashmi, Mohammad Areeb Qazi, Mohammad Yaqub:
MedMerge: Merging Models for Effective Transfer Learning to Medical Imaging Tasks. CoRR abs/2403.11646 (2024) - [i6]Santosh Sanjeev, Nuren Zhaksylyk, Ibrahim Almakky, Anees Ur Rehman Hashmi, Mohammad Areeb Qazi, Mohammad Yaqub:
FissionFusion: Fast Geometric Generation and Hierarchical Souping for Medical Image Analysis. CoRR abs/2403.13341 (2024) - [i5]Santosh Sanjeev, Fadillah Adamsyah Maani, Arsen Abzhanov, Vijay Ram Papineni, Ibrahim Almakky, Bartlomiej W. Papiez, Mohammad Yaqub:
TiBiX: Leveraging Temporal Information for Bidirectional X-ray and Report Generation. CoRR abs/2403.13343 (2024) - [i4]Mohammad Areeb Qazi, Ibrahim Almakky, Anees Ur Rehman Hashmi, Santosh Sanjeev, Mohammad Yaqub:
DynaMMo: Dynamic Model Merging for Efficient Class Incremental Learning for Medical Images. CoRR abs/2404.14099 (2024) - [i3]Mohammad Areeb Qazi, Anees Ur Rehman Hashmi, Santosh Sanjeev, Ibrahim Almakky, Numan Saeed, Mohammad Yaqub:
Continual Learning in Medical Imaging from Theory to Practice: A Survey and Practical Analysis. CoRR abs/2405.13482 (2024) - 2023
- [c2]Santosh Sanjeev
PECon: Contrastive Pretraining to Enhance Feature Alignment Between CT and EHR Data for Improved Pulmonary Embolism Diagnosis. MLMI@MICCAI (1) 2023: 434-443 - [c1]Sanoojan Baliah
Exploring the Transfer Learning Capabilities of CLIP in Domain Generalization for Diabetic Retinopathy. MLMI@MICCAI (1) 2023: 444-453 - [i2]Santosh Sanjeev, Salwa K. Al Khatib, Mai A. Shaaban
PECon: Contrastive Pretraining to Enhance Feature Alignment between CT and EHR Data for Improved Pulmonary Embolism Diagnosis. CoRR abs/2308.14050 (2023) - [i1]Sanoojan Baliah, Fadillah A. Maani, Santosh Sanjeev, Muhammad Haris Khan:
Exploring the Transfer Learning Capabilities of CLIP in Domain Generalization for Diabetic Retinopathy. CoRR abs/2308.14212 (2023)
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