A hybrid training method based on deep learning for medical images ...
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A hybrid training method based on deep learning for medical images classification. Abstract: Deep learning has gained remarkable results in many fields.
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A hybrid training method based on deep learning for medical images classification. Mingyuan Li†. School of Art and Science. Vanderbilt University. Nashville, TN ...
17,18 These methods have achieved good results in different medical image processing tasks, such as image classification, segmentation, and other tasks. ...
Therefore, this paper proposes a high-accuracy medical image classification method based on deep learning, which is called hybrid CQ-SVM. Specifically, we ...
A hybrid training method based on deep learning for medical images classification · Figures and Tables · Topics · 12 References · Related Papers ...
Abstract With the rapid development of modern med- ical science and technology, medical image classifica- tion has become a more and more challenging ...
This classification method for classifying medical imageries is utilized by many researchers [10], [11], [12]. Various diagnostic imaging is gradually used to ...
Medical image analysis using deep learning algorithms - PMC - NCBI
www.ncbi.nlm.nih.gov › PMC10662291
The utilization of DL mechanisms in medical image analysis encompasses various practical approaches, including generative adversarial networks (GANs), hybrid ...
Nov 7, 2023 · In this work, we propose a hybrid model for a general classification task that yields better performance in most of the cases compared to ...
Mar 10, 2023 · This study proposes an effective hybrid approach based on genomic image processing (GIP) techniques to rapidly detect COVID-19 while avoiding ...