Classification of Artifacts in Multimodal Fused Images using Transfer Learning with Convolutional Neural Networks

Based on the performance results obtained, the pre-trained DenseNet 169 model provides the highest accuracy among the other four used models.

Authors

Sitaramanjaneya Reddy Guntur (ORCID: https://orcid.org/0000-0002-3502-7348)
Sagar Imambi Shaik

Institutions

Vignan's Foundation for Science, Technology & Research (IN)

Publication Details

Journal: Current Medical Imaging Formerly Current Medical Imaging Reviews
Published: 2024-11-08
DOI: https://doi.org/10.2174/0115734056256872240909112137
Primary Topic: Advanced Image Fusion Techniques
Type: article
Field-Weighted Citation Impact: 0.00

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article

Classification of Artifacts in Multimodal Fused Images using Transfer Learning with Convolutional Neural Networks

Sitaramanjaneya Reddy Guntur, Sagar Imambi Shaik

Nov 8, 2024

Current Medical Imaging Formerly Current Medical Imaging Reviews

Advanced Image Fusion Techniques

article

Classification of Artifacts in Multimodal Fused Images using Transfer Learning with Convolutional Neural Networks

Sitaramanjaneya Reddy Guntur, Sagar Imambi Shaik

November 8, 2024article en

Abstract

Based on the performance results obtained, the pre-trained DenseNet 169 model provides the highest accuracy among the other four used models.

Current Medical Imaging Formerly Current Medical Imaging ReviewsVol. 20

Vignan's Foundation for Science, Technology & Research (IN)

Openalex Percentile: Top 68%

Advanced Image Fusion Techniques

DOI Open Access PDF OpenAlex

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Classification of Artifacts in Multimodal Fused Images using Transfer Learning with Convolutional Neural Networks — Sitaramanjaneya Reddy Guntur, Sagar Imambi Shaik · Current Medical Imaging Formerly Current Medical Imaging Reviews (2024) | TGRS Research Map | TGRS