公款 发表于 2025-3-21 18:55:43
书目名称Intelligent Computing and Block Chain影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0469499<br><br> <br><br>书目名称Intelligent Computing and Block Chain影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0469499<br><br> <br><br>书目名称Intelligent Computing and Block Chain网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0469499<br><br> <br><br>书目名称Intelligent Computing and Block Chain网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0469499<br><br> <br><br>书目名称Intelligent Computing and Block Chain被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0469499<br><br> <br><br>书目名称Intelligent Computing and Block Chain被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0469499<br><br> <br><br>书目名称Intelligent Computing and Block Chain年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0469499<br><br> <br><br>书目名称Intelligent Computing and Block Chain年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0469499<br><br> <br><br>书目名称Intelligent Computing and Block Chain读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0469499<br><br> <br><br>书目名称Intelligent Computing and Block Chain读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0469499<br><br> <br><br>种族被根除 发表于 2025-3-21 22:59:14
http://reply.papertrans.cn/47/4695/469499/469499_2.png侧面左右 发表于 2025-3-22 02:20:57
Intelligent Computing and Block Chain978-981-16-1160-5Series ISSN 1865-0929 Series E-ISSN 1865-0937myelography 发表于 2025-3-22 04:39:07
http://reply.papertrans.cn/47/4695/469499/469499_4.pngGIDDY 发表于 2025-3-22 11:21:47
Li Lin,Jiewei Wu,Pujin Cheng,Kai Wang,Xiaoying Tangablate 发表于 2025-3-22 14:55:59
http://reply.papertrans.cn/47/4695/469499/469499_6.pngEncapsulate 发表于 2025-3-22 20:49:20
http://reply.papertrans.cn/47/4695/469499/469499_7.png出处 发表于 2025-3-22 23:03:25
http://reply.papertrans.cn/47/4695/469499/469499_8.pngincarcerate 发表于 2025-3-23 02:14:08
Jiewei Wu,Yue Zhang,Weikai Huang,Li Lin,Kai Wang,Xiaoying TangSOBER 发表于 2025-3-23 08:38:59
BLU-GAN: Bi-directional ConvLSTM U-Net with Generative Adversarial Training for Retinal Vessel Segmere maps extracted from encoding path layers and the previous decoding up-convolutional layers and to replace the simple skip-connection used in the original U-Net. Moreover, we use densely connected convolutions in certain layers to strengthen feature propagation, encourage feature reuse, and substa