A Dual-Branches Multiscale Dynamic Partial Convolutional Attention Network for Remote Sensing Change Detection by Wenbin Tang, Shuli Cheng, Anyu Du

“…In addition, a bottom-up training strategy is applied to strengthen the completeness of change detection. Extensive experiments on three publicly available datasets demonstrate that, compared to other methods, our proposed approach achieves superior performance and detection results, while reducing parameters and computational complexity.…”
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YOLO-Tryppa: A Novel YOLO-Based Approach for Rapid and Accurate Detection of Small Trypanosoma Parasites by Davide Antonio Mura, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto

“…Early detection of Trypanosoma parasites is critical for the prompt treatment of trypanosomiasis, a neglected tropical disease that poses severe health and socioeconomic challenges in affected regions. …”
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Lightweight YOLOv8s-Based Strawberry Plug Seedling Grading Detection and Localization via Channel Pruning by CHEN Junlin, ZHAO Peng, CAO Xianlin, NING Jifeng, YANG Shuqin

“…To improve the detection efficiency and reduce the model's computational cost, the layer-adaptive magnitude-based pruning(LAMP) score-based channel pruning algorithm was applied to compress the base YOLOv8s model. …”
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YOLOv10n-Based Defect Detection in Power Insulators: Attention Enhancement and Feature Fusion Optimization by Zhihao Wei, Yan Wei

“…In modern power systems, insulators, as key components of transmission lines, are crucial for defect detection for the safe operation of power grids. Aiming at the problems of low efficiency of traditional manual detection, the vulnerability of traditional image processing methods to environmental interference, and the insufficient ability of existing deep learning models to detect small target defects under complex backgrounds, this paper proposes an improved target detection model based on YOLOv10n, which is the first time to integrate the spatial channel attention mechanism (SEAttention) with the up-sampling expansion operation (Patch Expanding) in the Neck part of the model. …”
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A low illumination target detection method based on a dynamic gradient gain allocation strategy by Zhiqiang Li, Jian Xiang, Jiawen Duan

“…To address these issues, this study introduces an efficient target detection method for low illumination, named DimNet. …”
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Research on Lightweight Open-Pit Mine Driving Obstacle Detection Algorithm Based on Improved YOLOv8s by Bo Xu, Wubin Xu, Bing Li, Hanwen Zhang, Yuanbin Xiao, Weixin Zhou

“…Improving the accuracy and speed of obstacle detection during driving is of great significance to ensuring the safety of mine automation construction and improving the efficiency of overall unmanned operations. …”
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Automated lumbar intervertebral disc identification and herniation detection in MR images using cascade CNN architecture by Md Abu Sayed, Ashiqur Rahman, Sadman Mohammad Nasif, Sudipto Halder, Akram Hossain, Hasan Ahmed, Muhammad Abdul Kadir

“…This study aims to develop an automated, accurate, and efficient system for the detection and classification of lumbar intervertebral disc herniation using deep learning models applied to axial and sagittal MR images. …”
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A Review of Machine Learning and Transfer Learning Strategies for Intrusion Detection Systems in 5G and Beyond by Kinzah Noor, Agbotiname Lucky Imoize, Chun-Ta Li, Chi-Yao Weng

“…This review systematically explores the application of machine learning (ML) models in the context of Intrusion Detection Systems (IDSs) for modern network security, particularly within 5G environments. …”
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Improved cancer detection through feature selection using the binary Al Biruni Earth radius algorithm by El-Sayed M. El-Kenawy, Nima Khodadadi, Marwa M. Eid, Ehsaneh Khodadadi, Ehsan Khodadadi, Doaa Sami Khafaga, Amel Ali Alhussan, Abdelhameed Ibrahim, Mohamed Saber

“…Abstract With the advancement of medical technology, a large amount of complex data on cancers is produced for diagnosing and treating cancers. …”
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Universal Method for Detecting Violations in the Integrity of a Digital Image Based on Analysis of Blocks of its Matrix by Bobok I., Kobozeva A.

“…Thus, the aim of the work is to increase the efficiency of identifying the fact of violation of image integrity by developing a universal expert method with low computational complexity. …”
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MAH-YOLO: an enhanced YOLOv8n framework for loess landslide detection with multi-attention mechanisms by Yuan Liang, Zhe Chen, Zhengbo Yu, Zhong Wang, Qingyun Ji, Ziqiong He, Dongsheng Zhong, Zhongchang Sun, Huadong Guo

“…This study proposes an enhanced target detection architecture, MAH-YOLO, designed for the precise identification of eolian landslides in complex environments. …”
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Sustainable phytoprotection: a smart monitoring and recommendation framework using Puma Optimization for potato pathogen detection by Amal H. Alharbi, Faris H. Rizk, Khaled Sh. Gaber, Marwa M. Eid, Marwa M. Eid, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Pushan Kumar Dutta, Doaa Sami Khafaga

“…In contrast, convergence analysis demonstrated PO-RBM’s computational efficiency relative to PSO, GWO, and GA alternatives. …”
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Research on Ship Feature Recognition and Tracking Method Based on Long-line Array Single-photon LiDAR by Ziqiang PENG, Han WANG, Ruikai XUE, Xiaokai SHE, Genghua HUANG

“…Owing to the inconsistency between the characteristics of surface ships and ground target, and the lack of relevant data sets, the current commonly used fitting methods cannot effectively perceive surface target characteristics. In this paper, an efficient target tracking method for ships is proposed based on the characteristics of single-photon point clouds and long-distance target detection. …”
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A Cascaded Ensemble Framework Using BERT and Graph Features for Emotion Detection From English Poetry by Praveen K. Kazipeta, Venkatrama Phani Kumar Sistla, Venkata Krishna Kishore Kolli

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Detection and functional assessment of structural variants using whole-genome re-sequencing data in Nellore cattle by Natalia A. Marín-Garzón, Lucio F. M. Mota, Giovana Vargas, Leonardo M. Arikawa, Larissa F. S. Fonseca, Gerardo A. Fernandes Júnior, Roberto Carvalheiro, Lucia G. Albuquerque

“…Abstract Ongoing advances in genome sequencing technologies have enabled the identification of numerous structural variants (SVs) in livestock genomes, which are the main determinants of complex traits due to their impact on gene expression. …”
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Nitrogen-rich covalent organic polymers for efficient solid phase extraction of nonsteroidal anti-inflammatory drugs from water samples by Yuqi Cheng, Jia Li, Xiaochen Xiu, Xinghua Teng, Wen Zhang, Lei Ji, Leilei Wang

“…In order to monitor trace levels of NSAIDs from complex water samples, development of facile and efficient sample pretreatment is of great significance. …”
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LDDFSF-YOLO11: A Lightweight Insulator Defect Detection Method Focusing on Small-Sized Features by Peng Shen, Keyu Mei, Huiqiong Cao, Yongxiang Zhao, Guoqing Zhang

“…In addition, a collaborative attention mechanism and a multi-scale feature fusion module (MDMF) are proposed to enhance the model’s ability to detect small-sized defects in remote and complex backgrounds, effectively solving the problems of missed detections, false detections, and poor adaptability to complex backgrounds. …”
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Enhanced Performance of Asymmetrically Clipped DC-Biased Optical OFDM Systems Using Adjacent Symbol Detection by Wei-Wen Hu

“…Compared to the direct current (DC) biased optical OFDM (DCO-OFDM) and asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) schemes, the asymmetrically clipped DC biased optical OFDM (ADO-OFDM) has demonstrated a better balance between optical power efficiency and spectrum efficiency. However, both the traditional ADO-OFDM and ADO-OFDM with iteration receiver suffer from an error floor issue when a lower DC bias is allocated to the DCO-OFDM branch. …”
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BEATS: Practical Audit Trail in Blockchain Systems by Bilal Alagha, Ilker Ozcelik

“…Results demonstrate that the RSA-based Cryptographic Accumulator significantly improves verification efficiency, achieving O(1) time and space complexity. …”
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Research on multi class pests identification and detection based on fusion attention mechanism with Mask-RCNN-CBAM by Xingwang Wang, Xingwang Wang, Xingwang Wang, Can Hu, Xufeng Wang, Hainie Zha, Xueyong Chen, Shanshan Yuan, Jing Zhang, Jianfeng Liao, Zhangying Ye

“…This study addresses challenges in agricultural pest detection, such as false positives and missed detections in complex environments, by proposing an enhanced Mask-RCNN model integrated with a Convolutional Block Attention Module (CBAM). …”
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