[1]
ディープラーニングとFDTD法を用いた誘電率分布推定逆問題
[2] Kaiming He, Xiangyu Zhang, Shaoqing Ren and Jian Sun,
"Deep Residual Learning for Image Recognition, "
https://arxiv.org/pdf/1512.03385, 2015.
[3] ResNet,
https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py
[4] PyTorch,
https://pytorch.org/
[5] torchvision,
https://github.com/pytorch/vision/
[6] 赤石雅典, PyTorch&深層学習プログラム, 日経BP, 2021.
[7] 桑原義彦, 電磁波による生体内イメージング -原理からMATLABを用いた数値解析まで-, コロナ社, 2022.
[8] コロナ社,
https://www.coronasha.co.jp/np/isbn/9784339009811/
[9] NICT, Database of Tissue Dielectric Properties for Electromagnetic Modeling of Human Body,
https://www2.nict.go.jp/cgi-bin/202303080003/public_html/index.py/
[10] IFAC-CNR, Dielectric Properties of Body Tissues,
http://niremf.ifac.cnr.it/tissprop/htmlclie/htmlclie.php
[11] UWCEM, Phantom Repository,
https://uwcem.ece.wisc.edu/phantomRepository.html
[12] E. Zastrow, S. K. Davis, M. Lazebnik, F. Kelcz, B. D. Van Veen, and S. C. Hagness,
"Database of 3D Grid-Based Numerical Breast Phantoms for use in Computational Electromagnetics Simulations,"
https://uwcem.ece.wisc.edu/MRIdatabase/InstructionManual.pdf
[13] 計算科学振興財団, FOCUSスパコン,
https://www.j-focus.or.jp/