Performance of Deep Feature Extraction Models after Applying Dual-GAN.

Performance of Deep Feature Extraction Models after Applying Dual-GAN.

<p>Performance of Deep Feature Extraction Models after Applying Dual-GAN.</p>

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Bibliographic Details
Main Author:	Priyanka Roy (14580479) (author)
Other Authors:	Fahim Mohammad Sadique Srijon (19751363) (author), Pankaj Bhowmik (6002078) (author)
Published:	2025
Subjects:	Medicine Cell Biology Genetics Cancer Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified world every year significantly improved precision significant class imbalance prioritizing stable performance planning treatment early medical image datasets leading diseases imposing handling class imbalance deep learning models brain tumor classification medical imaging data highly imbalanced data feature extraction techniques overall healthcare process overall classification process improving patient outcomes explainable ensemble approach gan mechanism facilitates classification process explainable ensemble gan mechanism techniques aid proposed mechanism ml techniques overall accuracy study proposes study presents study focuses specifically designed shown promise score demonstrate research identifies reliable model proposed pipeline original quality mri scans informative features incorporating grad frequently affected crucial role contributing parts clinical diagnosis benchmark ml based pipeline 15 %.
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