MedNAS: Multiscale Training-Free Neural Architecture Search for Medical Image Analysis

Deep neural networks have demonstrated impressive results in medical image analysis, but designing suitable architectures for each specific task is expertise dependent and time consuming. Neural architecture search (NAS) offers an effective means of discovering architectures. It has been highly succ...

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Veröffentlicht in:	IEEE transactions on evolutionary computation 2024-06, Vol.28 (3), p.668-681
Hauptverfasser:	Wang, Yan, Zhen, Liangli, Zhang, Jianwei, Li, Miqing, Zhang, Lei, Wang, Zizhou, Feng, Yangqin, Xue, Yu, Wang, Xiao, Chen, Zheng, Luo, Tao, Goh, Rick Siow Mong, Liu, Yong
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Computing costs Datasets Empirical analysis Evolutionary optimization Feature extraction Image analysis Image classification Image resolution Indicators Lesions Medical diagnostic imaging medical image classification Medical imaging Multiple objective analysis Neural architecture search neural architecture search (NAS) Neural networks Optimization Search algorithms training-free architecture search
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