FAD-Net: Automated Framework for Steel Surface Defect Detection in Urban Infrastructure Health Monitoring by Nian Wang, Yue Chen, Weiang Li, Liyang Zhang, Jinghong Tian

“…The MSDFConv module, employing multi-scale dilated convolutions with optimized dilation rates to preserve fine details while expanding the receptive field. …”
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A Novel Method for Intelligent Fault Diagnosis of Bearing Based on Capsule Neural Network by Zhijian Wang, Likang Zheng, Wenhua Du, Wenan Cai, Jie Zhou, Jingtai Wang, Xiaofeng Han, Gaofeng He

“…In order to accelerate the learning rate, the parameters which have bigger change are punished by cost function in the process of training. …”
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Large-Scale nighttime illuminated road extraction in the BTH region of China using SDGSAT-1 nighttime light data by Qiyuan Xie, Hui Li, Linhai Jing, Yichen Jiang, Haifeng Ding, Zhongchang Sun

“…The proposed model uses UNet as the basic architecture and incorporates a dynamic snake convolution module to increase the sensitivity of the NTIR pixels. …”
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SCH-Hunter: A Taint-Based Hybrid Fuzzing Framework for Smart Contract Honeypots by Haoyu Zhang, Baotong Wang, Wenhao Fu, Leyi Shi

“…A symbolic execution module is also introduced to resolve complex conditional branches that fuzzing alone fails to penetrate, enabling constraint solving. …”
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Cross-Domain Person Re-Identification Based on Multi-Branch Pose-Guided Occlusion Generation by Pengnan Liu, Yanchen Wang, Yunlong Li, Deqiang Cheng, Feixiang Xu

“…Firstly, a novel pose-guided occlusion generation module is designed to enhance the model’s ability to extract discriminative features from non-occluded areas. …”
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Cross-Layer Feature Fusion and Decentration Aberration Correction of Circular Points for Automated Guided Vehicle Terminal Positioning by Guiyang Zhang, Lanyu Yang, Kunkang Cao, Zengguang Man, Jian Wu, Boning Li

“…The experimental results demonstrated that the proposed method achieved dynamic positioning accuracy of better than 2.0 mm, static positioning accuracy of better than 1.5 mm, and a false recognition rate of less than 1.33% in the range of 3 m from AGV to the tray. …”
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Flow Regulation Characteristics of Active Flow-Regulating Vanes in U-Shaped Bends by LI Lin, ZHANG Jing-kai, ZHANG Lu-guo, CHI Miao-miao, XIAO Yu-lei

“…[Methods] The system combined a vertically adjustable and rotatable vane structure with a remote intelligent control module. It allowed real-time monitoring and dynamic adjustment of flow parameters, thereby overcoming the limitations of traditional fixed structures such as spur dikes and deflector vanes. …”
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Cattle welfare assessment based on adaptive fuzzy logic and multimodal data fusion by Lei Tong, Lei Tong, Lei Tong, Jiandong Fang, Jiandong Fang, Jiandong Fang, Xiuling Wang, Xiuling Wang, Xiuling Wang, Yudong Zhao, Yudong Zhao

“…Experimental validation shows that the method performs excellently across the three evaluation dimensions of environment, feeding, and behavior: the environment evaluation module achieves accuracy rates of 88.7% and 95.0% for the training and validation sets, respectively; the feeding evaluation module achieves 98.3% and 100%, respectively; and the behavior evaluation module achieves 85.7% and 93.6%. …”
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AITtrack: Attention-Based Image-Text Alignment for Visual Tracking by Basit Alawode, Sajid Javed

“…Extensive experiments are performed on six publicly available VOT benchmark datasets demonstrating the strong capabilities of our AITtrack by gaining an average success rate of 2.0%. Our code will be publicly available on: <uri>https://github.com/BasitAlawode/AITrack</uri>.…”
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Three-Dimensional Spatio-Temporal Slim Weighted Generative Adversarial Imputation Network: Spatio-Temporal Silm Weighted Generative Adversarial Imputation Net to Repair Missing Oce... by Yiwan Yue, Juan Li, Yu Zhang, Meiqi Ji, Jingyao Zhang, Rui Ma

“…The generator captures the three-dimensional spatial distribution and vertical profile dynamic patterns through the spatio-temporal attention module, while the discriminator introduces gradient penalty constraints to prevent gradient vanishing. …”
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Enhancing Reliability in Infrastructure-Based Collective Perception: A Dual-Channel Hybrid Delivery Approach With Real-Time Monitoring by Yu Asabe, Ehsan Javanmardi, Jin Nakazato, Manabu Tsukada, Hiroshi Esaki

“…Standalone autonomous vehicles primarily rely on their onboard sensors and may have blind spots or limited situational awareness in complex or dynamic traffic scenarios, leading to difficulties in making safe decisions. …”
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Apple Detection via Near-Field MIMO-SAR Imaging: A Multi-Scale and Context-Aware Approach by Yuanping Shi, Yanheng Ma, Liang Geng

“…Addressing challenges such as weak scattering, low texture contrast, and complex backgrounds in SAR images, we propose an innovative detection framework integrating Dynamic Spatial Pyramid Pooling (DSPP), Recursive Feature Fusion Network (RFN), and Context-Aware Feature Enhancement (CAFE) modules. …”
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U-shape-based network for left ventricular segmentation in echocardiograms with contrastive pretraining by Zhengkun Qian, Tao Hu, Jianming Wang, Zizhong Yang

“…Abstract Cardiovascular diseases, characterized by high morbidity, disability, and mortality rates, are a collective term for disorders affecting the heart’s structure or function. …”
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Local Linear Wavelet Neural Network–Based Unscented Kalman Filter for Vehicle Collision Estimate Warning System and Ensuring Stable Vehicle-to-Infrastructure Communication by Yonas Kebede Lema, Satyasis Mishra, Demissie J. Gelmecha

“…The accident mortality rates are rapidly increasing due to driver inattention, and traffic accidents become a significant problem on a global scale. …”
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Lightweight and efficient skeleton-based sports activity recognition with ASTM-Net. by Bin Wu, Mei Xue, Ying Jia, Ning Zhang, GuoJin Zhao, XiuPing Wang, Chunlei Zhang

“…To address these challenges, we propose ASTM‑Net, an Activity‑aware SpatioTemporal Multi‑branch graph convolutional network comprising two novel modules. First, the Activity‑aware Spatial Graph convolution Module (ASGM) dynamically models Activity‑Aware Adjacency Graphs (3A‑Graphs) by fusing a manually initialized physical graph, a learnable graph optimized end‑to‑end, and a dynamically inferred, activity‑related graph-thereby capturing evolving spatial affinities. …”
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Parvalbumin neurons enhance temporal coding and reduce cortical noise in complex auditory scenes by Jian Carlo Nocon, Howard J. Gritton, Nicholas M. James, Rebecca A. Mount, Zhili Qu, Xue Han, Kamal Sen

“…Here, we address these questions in auditory cortex of mice using a cocktail party-like paradigm, integrating electrophysiology, optogenetic manipulations, and a family of spike-distance metrics, to dissect parvalbumin neurons’ contributions towards rate and timing-based coding. We find that suppressing parvalbumin neurons degrades cortical discrimination of dynamic sounds in a cocktail party-like setting via changes in rapid temporal modulations in rate and spike timing, and over a wide range of time-scales. …”
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Automatic pine wilt disease detection based on improved YOLOv8 UAV multispectral imagery by Shaoxiong Xu, Wenjiang Huang, Dacheng Wang, Biyao Zhang, Hong Sun, Jiayu Yan, Jianli Ding, Jinjie Wang, Qiuli Yang, Tiecheng Huang, Xu Ma, Longlong Zhao, Zhuoqun Du

“…The improved YOLOv8 model used omni-dimensional dynamic convolution (ODConv) to enhance the performance of convolutional networks, designed a dynamic head (DyHead) module to capture PWD features more accurately, and applied MPDioU to improve the regression accuracy and model runtime efficiency. …”
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Flexi-YOLO: A lightweight method for road crack detection in complex environments. by Jiexiang Yang, Renjie Tian, Zexing Zhou, Xingyue Tan, Pingyang He

“…We designed Wise-IoU as the model's loss function to optimize the regression accuracy of its bounding boxes and enhance robustness to low-quality samples. The DCNv-C2f module is constructed for the transformation and fusion of feature information, allowing the convolutional kernels to adapt to the complex shape characteristics of cracks dynamically. …”
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AGW-YOLO-Based UAV Remote Sensing Approach for Monitoring Levee Cracks by HU Weibo, ZHOU Shaoliang, ZHAO Erfeng, ZHAO Xueqiang

“…The ADown module dynamically adapts its downsampling strategy according to the feature characteristics, effectively reducing the number of parameters and computational complexity, while enhancing the model's ability to capture crack edges and fine textural details. …”
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Optimizing peanut vine-inversion operations via intelligent control and semantic segmentation by Haiyang Shen, Man Gu, Hongguang Yang, Jie Ling, Lili Shi, Feng Wu, Fengwei Gu, Jiazhuang Tan, Zhichao Hu

“…In this system, the inversion rate derived from the semantic segmentation is used as a feedback signal to dynamically adjust the speeds of the conveyor belt and inversion roller in real time, thereby achieving closed‑loop control of the inversion process. …”
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