MSPB-YOLO: High-Precision Detection Algorithm of Multi-Site Pepper Blight Disease Based on Improved YOLOv8 by Xiaodong Zheng, Zichun Shao, Yile Chen, Hui Zeng, Junming Chen

“…By incorporating the RVB-EMA module into the model, we can significantly reduce interference from shallow noise in high-resolution depth layers. …”
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An Improved YOLOv8-Based Dense Pedestrian Detection Method with Multi-Scale Fusion and Linear Spatial Attention by Han Gong, Tian Li, Lijuan Wang, Shucheng Huang, Mingxing Li

“…Simultaneously, a multi-scale linear spatial attention module is designed to amplify features of visible parts of occluded pedestrians while suppressing interference from complex backgrounds. …”
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SmartPod: An Automated Framework for High-Precision Soybean Pod Counting in Field Phenotyping by Fei Liu, Shudong Wang, Shanchen Pang, Zhongzhi Han, Longgang Zhao

“…Accurate soybean pod counting remains a significant challenge in field-based phenotyping due to complex factors such as occlusion, dense distributions, and background interference. We present SmartPod, an advanced deep learning framework that addresses these challenges through three key innovations: (1) a novel vision Transformer architecture for enhanced feature representation, (2) an efficient attention mechanism for the improved detection of overlapping pods, and (3) a semi-supervised learning strategy that maximizes performance with limited annotated data. …”
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Comparative Studies of Descriptor-Based Image Matching Techniques for AAV Applications by Tomasz Pogorzelski, Teresa Zielinska

“…This article presents the results of comparative studies of typical image feature-matching algorithms. Pre-processed images recorded during flights and satellite orthophotomaps are used for these studies. …”
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The application of deep learning technology in smart agriculture: Lightweight apple leaf disease detection model by Luo Man

“…Built on the YOLOv8 architecture, the model incorporates a refined backbone with the EdgeNeXt network, enhancing feature extraction for improved identification precision. …”
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Multi-label classification for image tamper detection based on Swin-T segmentation network in the spatial domain by Li Li, Kejia Zhang, Jianfeng Lu, Shanqing Zhang

“…Our method introduces three key innovations: (1) A spatial perception module that combines the spatial rich model (SRM) with constrained convolution, enabling focused detection of tampering traces while suppressing interference from image content; (2) A hierarchical feature learning architecture that integrates Swin Transformer with UperNet for effective multi-scale tampering pattern recognition; and (3) A comprehensive optimization strategy including auxiliary supervision, self-supervised learning, and hard example mining, which significantly improves model convergence and detection accuracy. …”
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Biotronik Implantable Cardioverter Defibrillator for Measurement of Intrathoracic Impedance: A Report of Two Cases by Xuqing Ying, Xinyue Yu, Weixun Cai, Xiaomin Chen, Lihua Wang, Qingcheng Wang, Jie Pang

“…Conclusions This phenomenon should not be regarded as an interference signal or an abnormal sign of pacemaker malfunction.…”
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Fault diagnosis model of rolling bearings based on the M-YOLO network by NING Shaohui, ZHANG Shaopeng, WU Yukun, DU Yue, FAN Xiaoning

“…The rolling bearing is taken as the research object, and the fault diagnosis algorithm with two-dimensional signal as the input is studied, and the fault diagnosis model of rolling bearing based on M-YOLO network is constructed for the problems of multi-condition fault diagnosis, small data sample, and long model training time.MethodsFirstly, the mosaic data augmentation method was used to enrich the samples to improve the interference of unbalanced data on the diagnostic results. …”
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Determination of fracture mechanics parameters on a base of local displacement measurements by Yu. G. Matvienko, V.S. Pisarev, S. I. Eleonsky

“…An availability of high-quality interference fringe patterns, which are free from rigid-body motions, serves as a reliable indicator of real stress state around a crack tip. …”
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Camera-Adaptive Foreign Object Detection for Coal Conveyor Belts by Furong Peng, Kangjiang Hao, Xuan Lu

“…CAFOD incorporates three main strategies: (1) Multi-View Data Augmentation (MVDA) simulates viewpoint variations during training, enabling the model to learn robust, viewpoint-invariant features; (2) Context Feature Perception (CFP) integrates local coal background information to reduce false detections outside the conveyor belt; and (3) Conveyor Belt Area Loss (CBAL) enforces explicit attention to the conveyor belt region, minimizing background interference. …”
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Failure or future? Exploring alternative antibacterials: a comparative analysis of antibiotics and naturally derived biopolymers by Artemijs Sceglovs, Artemijs Sceglovs, Ingus Skadins, Marco Chitto, Juta Kroica, Kristine Salma-Ancane, Kristine Salma-Ancane

“…This review critically examines naturally derived biopolymers with intrinsic (essential feature) antibacterial properties as a sustainable, next-generation alternative to traditional antibiotics. …”
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Design and Implementation of an Intelligent Pest Status Monitoring System for Farmland by Xinyu Yuan, Zeshen He, Caojun Huang

“…For overlapping pest detection, EfficientNetv2-S replaces the YOLOv5s backbone and is combined with an Adaptive Feature Pyramid Network (AFPN), achieving 95.72% detection accuracy, 94.04% mAP, and 127 FPS. …”
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Multi-Scale Construction Site Fire Detection Algorithm with Integrated Attention Mechanism by Haipeng Sun, Tao Yao

“…An iCBAM attention module is designed to suppress background noise interference and enhance the representation capability of the network. …”
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Molten Pool Image Segmentation Based on Adaptive Multi-Scale Attention Mechanism by Yuefeng Chen, Weihua Liu, Qing Yang, Huabin Chen, Qi Jiang

“…This study presents an innovative segmentation algorithm that seamlessly integrates an adaptive multi-scale attention mechanism with the Lossab loss function to tackle challenges like overlapping molten pool contours and arc interference during image segmentation. Initially, an adaptive multi-scale channel attention mechanism is introduced and fused with a feature pyramid, forming a multi-scale attention pyramid structure that significantly enhances the network’s capability to extract intricate molten pool features. …”
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Exploring a multi-path U-net with probability distribution attention and cascade dilated convolution for precise retinal vessel segmentation in fundus images by Ruihong Zhang, Guosong Jiang

“…A CDCM is integrated to gather multi-scale vessel features, enhancing the model’s ability to extract deep semantic features. …”
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Deblurring Method of Face Recognition AI Technology Based on Deep Learning by Weilong Li, Jie Li, Junhui Zhou

“…As a common method of deep learning, a convolutional neural network (CNN) shows excellent performance in face recognition. The features extracted by traditional face recognition methods are greatly influenced by subjective factors and are time-consuming and laborious. …”
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Anti-Chaff Jamming Method of Radar Based on Real Dataset and Residual Attention Model by Shuolei Li, Bin Liu, Lin Zhou, Jingping Liu

“…As a typical and widely used passive jamming method, chaff clouds have a strong interference effect on radar that remains a significant challenge effectively to counteract. …”
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Deep Learning-Based Active Jamming Suppression for Radar Main Lobe by Yilin Jiang, Yaozu Yang, Wei Zhang, Limin Guo

“…By first filtering out interference-related features and then reconstructing the signal, we can achieve better jamming suppression performance. …”
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DISCUSSIONS ON THE JUST WORLD ORDER IN TURKEY: COMPARATIVE ANALYSIS OF CONCEPTS AND FOREIGN POLICY PRACTICES OF THEIR IMPLEMENTATION IN THE 2000’s by P. V. Shlykov

“…Polycentric structural organization, an intrinsic feature of the Middle East, has resulted in multiple visions of regional order generated by regional powers and global actors actively involved in the regional affairs. …”
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Hierarchical Information-guided robotic grasp detection by Zeyao Hou, Yueran Zhao, Yutao Jin, Chao Yang, Zongyu He, Xiaoyan Chen

“…To address these issues, we propose GraspFormer, a novel method for robotic grasp detection. GraspFormer features a unique Encoder-Decoder framework that incorporates a Grasp Transformer Block designed to model long-range dependencies while avoiding background interference. …”
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