RESIGN: Alzheimer's Disease Detection Using Hybrid Deep Learning based Res-Inception Seg Network

The proposed RESIGN model demonstrates significant improvement in early AD detection through robust feature extraction and classification by offering a reliable tool for clinical diagnosis.

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Publication Details

Journal
Current Alzheimer Research
Published
2025-06-20
DOI
https://doi.org/10.2174/0115672050373821250612053943
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.00
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article

RESIGN: Alzheimer's Disease Detection Using Hybrid Deep Learning based Res-Inception Seg Network

K. Amsavalli, S. Sudha, S. Kanaga Suba Raja
Current Alzheimer Research
Brain Tumor Detection and Classification
article

RESIGN: Alzheimer's Disease Detection Using Hybrid Deep Learning based Res-Inception Seg Network

K. Amsavalli, S. Sudha, S. Kanaga Suba Raja
article en

Abstract

The proposed RESIGN model demonstrates significant improvement in early AD detection through robust feature extraction and classification by offering a reliable tool for clinical diagnosis.

Current Alzheimer ResearchVol. 22(9)
SRM Institute of Science and Technology (IN), Anna University, Chennai (IN)
Good health and well-being
Openalex Percentile: Top 81%
Brain Tumor Detection and Classification
DOISourceOpenAlex
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RESIGN: Alzheimer's Disease Detection Using Hybrid Deep Learning based Res-Inception Seg Network — K. Amsavalli, S. Sudha, et al. · Current Alzheimer Research (2025) | TGRS Research Map | TGRS