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Which model to transfer? a survey on transferability estimation
Transfer learning methods endeavor to leverage relevant knowledge from existing source
pre-trained models or datasets to solve downstream target tasks. With the increase in the …
pre-trained models or datasets to solve downstream target tasks. With the increase in the …
One size does not fit all in evaluating model selection scores for image classification
Selecting pretrained models for image classification often involves computationally intensive
finetuning. This study addresses a research gap in the standardized evaluation of …
finetuning. This study addresses a research gap in the standardized evaluation of …
On dataset transferability in medical image classification
Current transferability estimation methods designed for natural image datasets are often
suboptimal in medical image classification. These methods primarily focus on estimating the …
suboptimal in medical image classification. These methods primarily focus on estimating the …
RAIDER: Rapid AI Diagnosis at Edge using Ensemble Models for Radiology
Chest X-rays have played an indispensable part in medical diagnosis for several decades.
However, there is a scarcity of experts who can interpret these images to diagnose critical …
However, there is a scarcity of experts who can interpret these images to diagnose critical …
Analyzing and Improving the Robustness of Machine Learning Models to Distribution Shifts
A Mehra - 2024 - search.proquest.com
Abstract Machine Learning (ML) models, at the forefront of innovation, are revolutionizing
safety-critical domains like self-driving cars, medical diagnostics, and drone-based rescue …
safety-critical domains like self-driving cars, medical diagnostics, and drone-based rescue …