粘上 发表于 2025-3-21 17:19:07
书目名称Vector Optimization影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0980841<br><br> <br><br>书目名称Vector Optimization影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0980841<br><br> <br><br>书目名称Vector Optimization网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0980841<br><br> <br><br>书目名称Vector Optimization网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0980841<br><br> <br><br>书目名称Vector Optimization被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0980841<br><br> <br><br>书目名称Vector Optimization被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0980841<br><br> <br><br>书目名称Vector Optimization年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0980841<br><br> <br><br>书目名称Vector Optimization年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0980841<br><br> <br><br>书目名称Vector Optimization读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0980841<br><br> <br><br>书目名称Vector Optimization读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0980841<br><br> <br><br>凹处 发表于 2025-3-21 20:50:16
uman model actuated by numerous skeletal muscles, with two human-like eyes whose retinas have spatially nonuniform distributions of photoreceptors. Our prototype sensorimotor system for this model incorporates a set of 20 automatically-trained, deep neural networks (DNNs), half of which are neuromusCAGE 发表于 2025-3-22 04:29:31
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shapes) or hand movements (hand gestures). Such a hand interface system can be realized by using cameras as input devices, and software for analyzing the images. In this hand interface system, commands are recognized by analyzing the hand shapes and its trajectories in the images. Therefore, succes发出眩目光芒 发表于 2025-3-22 16:39:19
n requires a significant amount of the supervisory surgeons’ time, and it can be a very subjective decision. This study uses an object detection algorithm, Scaled-YOLOv4, in conjunction with a centroid tracking algorithm to evaluate the surgeon’s skills during advanced intracorporeal suturing. We pr群岛 发表于 2025-3-22 17:26:42
ith a focus on establishing the superiority of hybrid transformer architectures. The models include autoencoder, convolutional autoencoder, temporal autoencoder (GRU autoencoder), transformer, convolutional transformer, and transformer with a convolutional encoder, representing diverse approaches inMUTE 发表于 2025-3-22 21:19:34
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