fundoplication
发表于 2025-3-21 16:17:14
书目名称Advanced Intelligent Computing Technology and Applications影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0167162<br><br> <br><br>书目名称Advanced Intelligent Computing Technology and Applications影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0167162<br><br> <br><br>书目名称Advanced Intelligent Computing Technology and Applications网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0167162<br><br> <br><br>书目名称Advanced Intelligent Computing Technology and Applications网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0167162<br><br> <br><br>书目名称Advanced Intelligent Computing Technology and Applications被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0167162<br><br> <br><br>书目名称Advanced Intelligent Computing Technology and Applications被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0167162<br><br> <br><br>书目名称Advanced Intelligent Computing Technology and Applications年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0167162<br><br> <br><br>书目名称Advanced Intelligent Computing Technology and Applications年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0167162<br><br> <br><br>书目名称Advanced Intelligent Computing Technology and Applications读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0167162<br><br> <br><br>书目名称Advanced Intelligent Computing Technology and Applications读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0167162<br><br> <br><br>
黄瓜
发表于 2025-3-21 21:59:05
MAPNet: A Multi-scale Attention Pooling Network for Ultrasound Medical Image Segmentationnt autonomous feature extraction capability and good feature representation ability. Traditional convolutional neural networks usually use standard convolutional layers to extract features. However, in medical image segmentation, a pixel may correspond to multiple different scale structures, such as
Acumen
发表于 2025-3-22 02:47:16
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欲望小妹
发表于 2025-3-22 05:16:18
MOD-YOLO: Improved YOLOv5 Based on Multi-softmax and Omni-Dimensional Dynamic Convolution for Multi- of bridge defect categories often occurs simultaneously, it is difficult for target detection methods targeting a single label to achieve accurate bridge defect detection. This paper proposes a bridge defect detection scheme YOLOv5 based on multi-softmax and omni-dimensional dynamic convolution (MO
空气传播
发表于 2025-3-22 11:26:27
Color Image Steganography Based on Two-Channel Preprocessing and U-Net Networkrocess where secret information may be stolen. With the increasing application of the U-Net network, a novel image steganography technique based on the U-Net structure is designed. The special two-channel preprocessing network is designed to fuse image features, and the SENet attention mechanism has
Axon895
发表于 2025-3-22 16:32:47
Application of a Hybrid Particle Image Velocimetry Method Based on Window Function in the Field of Te initial velocity field generated based on cross-correlation algorithm in mixed particle image velocimetry methods. This can result in inaccurate offset images generated, leading to errors in generating the final fine velocity field using optical flow method. This article adds a window function to
绿州
发表于 2025-3-22 17:03:35
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Gum-Disease
发表于 2025-3-23 01:12:37
Refinement Correction Network for Scene Text Detectionliability of text detection. To this end, existing models primarily employ deep convolutional networks to extract semantic information from images. However, the multiple convolutions and downsampling operations in network lead to varying degrees of defects in shallow and deep features. To address th
救护车
发表于 2025-3-23 01:40:51
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蔓藤图饰
发表于 2025-3-23 06:34:03
Unsupervised Extremely Low-Light Image Enhancement with a Laplacian Pyramid Network. To overcome these two problems, we propose an unsupervised Extremely Low-light image enhancement via a Laplacian Pyramid Network (ELLPN). Concretely, concerning the first quandary, we propose to enforce semantic content and style constraints in the low-frequency components of the image’s Laplacian