文献
J-GLOBAL ID:202202261059167911
整理番号:22A1055797
SSRNet:パラメータ削減のためのスパース接続と重み共有に基づくCT再構成ネットワーク【JST・京大機械翻訳】
SSRNet: A CT Reconstruction Network Based on Sparse Connection and Weight Sharing for Parameters Reduction
著者 (5件):
Yan Diwei
(School of Biological Science & Medical Engineering, Southeast University, Nanjing, China)
,
Zhao Qingxian
(School of Biological Science & Medical Engineering, Southeast University, Nanjing, China)
,
Zheng Liang
(School of Biological Science & Medical Engineering, Southeast University, Nanjing, China)
,
Zhou Xuefeng
(School of Biological Science & Medical Engineering, Southeast University, Nanjing, China)
,
Luo Shouhua
(School of Biological Science & Medical Engineering, Southeast University, Nanjing, China)
資料名:
Sensing and Imaging
(Sensing and Imaging)
巻:
23
号:
1
ページ:
14
発行年:
2022年
JST資料番号:
W4938A
ISSN:
1557-2072
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
ドイツ (DEU)
言語:
英語 (EN)