Investigation of thermal-mechanical performance of dual-chip SiC power devices based on Cu clip interconnection by LIAO Linjie, FAN Yi, MEI Xiaoyang, WANG Liancheng

“…This leads to high parasitic inductance and reliability issues, limiting the development of silicon carbide (SiC) power devices. …”
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Liver segmentation network based on detail enhancement and multi-scale feature fusion by Lu Tinglan, Qin Jun, Qin Guihe, Shi Weili, Zhang Wentao

“…The MSFF module enhances the capture of global features, thus improving the accuracy of the liver segmentation model. …”
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MDCFVit-YOLO: A model for nighttime infrared small target vehicle and pedestrian detection. by Huiying Zhang, Qinghua Zhang, Yifei Gong, Feifan Yao, Pan Xiao

“…An MDCFVit-YOLO model based on the YOLOv8 algorithm is proposed to address issues in nighttime infrared object detection such as low visibility, high interference, and low precision in detecting small objects. …”
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A Novel Framework for Remote Sensing Image Synthesis with Optimal Transport by Jinlong He, Xia Yuan, Yong Kou, Yanci Zhang

“…Remote sensing images (RSIs) are characterized by large intraclass variance and small interclass variance, which pose significant challenges for image synthesis. To address these issues, we design and incorporate two distinct attention modules into our GAN framework. …”
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IMP‐DETR: Optimization model for defect detection of injection‐moulded products by Anzhan Liu, Lei Han

“…Additionally, the Conv3XC‐Fusion module is designed to resolve the problem of integrating multi‐scale features, improving the stability of detection. …”
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A Fractal Curve-Inspired Framework for Enhanced Semantic Segmentation of Remote Sensing Images by Xinhua Wang, Botao Yuan, Zhuang Li, Heqi Wang

“…The classification and recognition of features play a vital role in production and daily life; however, the current semantic segmentation of remote sensing images is hampered by background interference and other factors, leading to issues such as fuzzy boundary segmentation. To address these challenges, we propose a novel module for encoding and reconstructing multi-dimensional feature layers. …”
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A Study on New Generation Electro-pneumatic Braking Control Technology for Autonomous-rail Rapid Tram by LIANG Peng, YU Jieren, LUO Xiaofeng, LI Taipeng

“…In the pressure regulation integrated module section, multiple functional valves such as pressure regulating valve, emergency solenoid valve, and remote relief valve are integrated into one module. …”
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Brightness adjustment and contrast matching in low-light underwater images using feedforward neural networks by Zahra Raeisi, Reza Ahmadi Lashaki, Maryam Deldadehasl, Alireza Golkarieh, Maral mirza Mohammadi

“…Light scattering and light absorption are two fundamental issues in improving the quality of underwater images. …”
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Multi-Scale Convolutional Attention and Structural Re-Parameterized Residual-Based 3D U-Net for Liver and Liver Tumor Segmentation from CT by Ziwei Song, Weiwei Wu, Shuicai Wu

“…By incorporating a structural re-parameterized residual module (ELANRes) and a multi-scale convolutional attention module (MSCA), the network significantly improves feature extraction and boundary optimization, particularly excelling in segmenting small targets. …”
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Hierarchical Modeling for Medical Visual Question Answering with Cross-Attention Fusion by Junkai Zhang, Bin Li, Shoujun Zhou

“…The framework also incorporates a cross-attention fusion module where images serve as queries and text as key-value pairs. …”
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TDFNet: twice decoding V-Mamba-CNN Fusion features for building extraction by Wenlong Wang, Peng Yu, Mengmeng Li, Xiaojing Zhong, Yuanrong He, Hua Su, Yunxuan Zhou

“…To address these issues, this paper introduces a novel extraction method called TDFNet. …”
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Eternal-MAML: a meta-learning framework for cross-domain defect recognition by Jipeng Feng, Haigang Zhang, Zhifeng Wang

“…This article proposes a novel MAML framework, termed as Eternal-MAML, which guides the update of the classifier module by learning a meta-vector that shares commonality across batch tasks in the inner loop, and addresses the overfitting phenomenon caused by label arrangement issues in testing phase for vanilla MAML. …”
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A fish counting model based on pyramid vision transformer with multi-scale feature enhancement by Jiaming Xin, Yiying Wang, Dashe Li, Zhongliang Xiang

“…This mechanism facilitates information exchange between areas of low and high fish density, addressing the issue of nonuniform density distribution. Subsequently, a spatial domain multi-scale edge enhancement module is introduced to enhance the detection of fish edge features. …”
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Constraining Free Merge by Jason Ginsburg

“…I attempt to demonstrate that, within the confines of the language module, Labeling is generally sufficient to constrain Free Merge, and I discuss issues that arise regarding overgeneration of syntactic structures given Free Merge.…”
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Pretraining-improved Spatiotemporal graph network for the generalization performance enhancement of traffic forecasting by Xiangyue Zhang, Chao Li, Ling Ji, Yuyun Kang, Mingming Pan, Zhuo Liu, Qiang Qi

“…A key challenge is capturing the long-term spatiotemporal dependencies of traffic data while improving the model’s generalization ability. To address these issues, various sophisticated modules are embedded into different models. …”
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Feature-Separated Lightweight Model for Road Extraction in Wild Environments by Che Shi, Yuefeng Cen, Gang Cen

“…A Feature Separation and Enhancement Module (FSEM) independently processes spatial and channel features, while a Feature Aggregation Module (FAM) integrates multi-scale features for improved road continuity and accuracy. …”
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PoseNet++: A multi-scale and optimized feature extraction network for high-precision human pose estimation. by Chao Lv, Geyao Ma

“…Human pose estimation (HPE) has made significant progress with deep learning; however, it still faces challenges in handling occlusions, complex poses, and complex multi-person scenarios. To address these issues, we propose PoseNet++, a novel approach based on a 3-stacked hourglass architecture, incorporating three key innovations: the multi-scale spatial pyramid attention hourglass module (MSPAHM), coordinate-channel prior convolutional attention (C-CPCA), and the PinSK Bottleneck Residual Module (PBRM). …”
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Manhattan Correlation Attention Network for Metal Part Anomaly Classification by Zijiao Sun, Yanghui Li, Fang Luo, Zhiliang Zhang, Jiaqi Huang, Qiming Zhang

“…However, it is difficult to detect metal anomalies due to the following issues: 1) Some defects of metal parts areas are small; 2) The abnormal metal regions are relatively similar to the normal ones. …”
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Improved YOLOv8n based helmet wearing inspection method by Xinying Chen, Zhisheng Jiao, Yuefan Liu

“…The YOLOv8 C2f module is enhanced with a new SC_Bottleneck structure, incorporating the SCConv module, now termed SC_C2f, to mitigate model complexity and computational costs. …”
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GMTBLC: a deep learning-based bi-modal network traffic classification method by WEI Debin, JIANG Qinlong, WEN Jinglong, WANG Xinrui

“…In the classification phase, the images were firstly processed by the packet group mix transformer (PCMT) module, which utilized the transformer and GMA to capture global features. …”
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