Normalization-Guided and Gradient-Weighted Unsupervised Domain Adaptation Network for Transfer Diagnosis of Rolling Bearing Faults Under Class Imbalance by Hao Luo, Xinyue Wang, Li Zhang

“…Firstly, the proposed network integrates a residual feature extractor with the Domain Normalization (DN) module to enhance domain-invariant feature extraction. …”
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Stealthy Vehicle Adversarial Camouflage Texture Generation Based on Neural Style Transfer by Wei Cai, Xingyu Di, Xin Wang, Weijie Gao, Haoran Jia

“…However, most of the existing adversarial camouflage textures that attack object detection models only consider the effectiveness of the attack, ignoring the stealthiness of adversarial attacks, resulting in the generated adversarial camouflage textures appearing abrupt to human observers. To address this issue, we propose a style transfer module added to an adversarial texture generation framework. …”
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Weamba: Weather-Degraded Remote Sensing Image Restoration with Multi-Router State Space Model by Shuang Wu, Xin He, Xiang Chen

“…Specifically, we develop a local-enhanced state space module to better aggregate rich local and global information, both of which are complementary and beneficial for high-quality image reconstruction. …”
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Digital mapping of soil electrical conductivity for paddy field by The Anh Anh, Luu Trong Hieu, Chi Ngon Nguyen

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Learners’ Feedback on the Effectiveness of Replacing an Instructional MOOC Video with Augmented Reality in a Practice-Based Course by Surendheran Kaliyaperumal, Mallika Vijayakumar

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VFQB: A Novel Deep Learning Model for Rolling Bearing Fault Diagnosis by Zhiru Xiao, Yanfang Xu, Junjie Cui

“…Next, a Bidirectional Gated Recurrent Unit (BiGRU) module is introduced to capture the temporal characteristics of the feature signals. …”
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A flare removal network for night vision perception: Resistant to the interference of complex light by Yan Liu, Guan Huang, Wenting Qi, Yujie Li

“…Abstract The high‐precision visual perception results are easily affected by the lens flare issue when the image sensor is facing to strong light. …”
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MobileDepth: Monocular Depth Estimation Based on Lightweight Vision Transformer by Yundong Li, Xiaokun Wei

“…To address the aforementioned difficulties, in this study, we propose a Dilated Self Attention Block (DSAB) as well as a Local and Global Feature Extraction (LGFE) module. The former resolves the inference speed issue of standard ViT models, and we accomplish this by limiting the number of self-attention computations among tokens. …”
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Deadbeat Predictive Current Control Strategy for Permanent Magnet-Assisted Synchronous Reluctance Motor Based on Adaptive Sliding Mode Observer by Bo Gao, Guoqiang Zhang, Gaolin Wang, Dianguo Xu

“…The adaptive control parameter module suppresses the chattering phenomenon in sliding mode control and enhances the observer’s adaptability under varying load conditions. …”
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Enhanced hybrid CNN and transformer network for remote sensing image change detection by Junjie Yang, Haibo Wan, Zhihai Shang

“…Secondly, the frequency component of these features is exploited by a refined module I. Thirdly, an enhanced token mining module based on the Kolmogorov-Arnold Network is utilized to derive semantic information. …”
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Measuring, Monitoring, Evaluating Slovenian Libraries: BibSiSt and e-Razvid by Eva Kodrič-Dačić

“…On the basis of the Minimum Standard Guidelines for Public Library Service in Slovenia a methodology for libraries' measurement and formulation of opinions issued by the Library System Development Centre was developed followed by the module for measuring library development and progress. …”
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LGFUNet: A Water Extraction Network in SAR Images Based on Multiscale Local Features with Global Information by Xiaowei Bai, Yonghong Zhang, Jujie Wei

“…The LGFUNet model consists of three parts: the encoder–decoder, the DECASPP module, and the LGFF module. In the encoder–decoder, the Swin-Transformer module is used instead of convolution kernels for feature extraction, enhancing the learning of global information and improving the model’s ability to capture the spatial features of continuous water bodies. …”
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Image dehazing algorithm based on deep transfer learning and local mean adaptation by Dongyang Shi, Sheng Huang

“…The framework consists of several key modules: an atmospheric light estimation module based on deep transfer learning, a transmission map estimation module utilizing local mean adaptation, a haze-free image reconstruction module, an image enhancement module, and a noise reduction module. …”
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Optimization Strategy for Underwater Target Recognition Based on Multi-Domain Feature Fusion and Deep Learning by Yanyang Lu, Lichao Ding, Ming Chen, Danping Shi, Guohao Xie, Yuxin Zhang, Hongyan Jiang, Zhe Chen

“…The network includes the TriFusion block module, the novel lightweight attention residual network (NLARN), the long- and short-term attention (LSTA) module, and the Mamba module. …”
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Feature Multi-Scale Enhancement and Adaptive Dynamic Fusion Network for Infrared Small Target Detection by Zenghui Xiong, Zhiqiang Sheng, Yao Mao

“…This model is based on a U-Net architecture and incorporates a Residual Multi-Scale Feature Enhancement (RMFE) module and an Adaptive Feature Dynamic Fusion (AFDF) module. …”
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GAB-YOLO: a lightweight deep learning model for real-time detection of abnormal behaviors in juvenile greater amberjack fish by Mingxin Liu, Mingxin Liu, Chun Zhang, Cong Lin, Cong Lin

“…First, we introduce the SobelMaxDS module, designed to enhance the network’s ability to extract edge and spatial features, thereby enabling more effective capture of the fish’s behavioral contours and preserving rich target information. …”
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Lightweight blasthole image detection and positioning method by Shan PAN, Ting YU, Zhongwen YUE, Zijian TIAN, Qingyu JIN

“…Finally, the loss function is optimized to improve the accuracy of blasthole bounding box regression. To tackle the issues of large parameter size and low frames per second (FPS) in the blasthole image detection and localization algorithm network model, a lightweight Sc_C2f module is proposed to optimize the network structure. …”
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CME Velocity Field Calculation Model Based on an Unsupervised Transformer Optical Flow Network by Qingyang Chen, Hong Lin, Zhenping Qiang, Hui Liu, Kaifan Ji, Zhenhong Shang

“…The network comprises a multiscale feature extraction module and a coarse-to-fine global optical flow calculation module. …”
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MCIDN: Deblurring Network for Metal Corrosion Images by Jiaxiang Wang, Meng Wan, Pufen Zhang, Sijie Chang, Hao Du, Peng Shi, Hongying Yu, Dongbai Sun, Jue Wang, Yangang Wang

“…While self-attention is widely used in visual tasks, its quadratic complexity often leads to high computational costs. To address this issue, we introduce a new spatial channel attention module (SCAM) that employs dynamic group convolutions to achieve self-attention, effectively integrating information from local regions and enhancing representation learning capabilities. …”
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Deep Learning-Based Algorithm for Road Defect Detection by Shaoxiang Li, Dexiang Zhang

“…First, it replaces the C2f module in the GD mechanism with the improved C2f module based on RepViTBlock to construct the Rep-GD module. …”
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