DM-YOLO: improved YOLOv9 model for tomato leaf disease detection by Abudukelimu Abulizi, Junxiang Ye, Halidanmu Abudukelimu, Wenqiang Guo

“…Therefore, an improved tomato leaf disease detection method, DM-YOLO, based on the YOLOv9 algorithm, is proposed in this paper. …”
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Ensemble-based eye disease detection system utilizing fundus and vascular structures by Hongjie Yu, Xingbo Dong

“…By using vascular features and mitigating the risk of overfitting, this framework demonstrates superior performance in terms of multiple metrics. …”
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A Dynamic Mode Decomposition Based Edge Detection Method for Art Images by Chongke Bi, Ye Yuan, Ronghui Zhang, Yiqing Xiang, Yuehuan Wang, Jiawan Zhang

“…Edge detection is a widely used feature extraction method in various fields, such as image processing, computer vision, machine vision, and so forth. …”
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Enhanced Detection of Leishmania Parasites in Microscopic Images Using Machine Learning Models by Michael Contreras-Ramírez, Jhonathan Sora-Cardenas, Claudia Colorado-Salamanca, Clemencia Ovalle-Bracho, Daniel R. Suárez

“…This study addresses the development of a system based on machine learning algorithms to detect <i>Leishmania</i> spp. parasite in direct smear microscopy images, contributing to the diagnosis of cutaneous leishmaniasis. …”
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Hybrid CNN-LSTM With Attention Mechanism for Robust Credit Card Fraud Detection by Iman Akour, Nour Mohamed, Said Salloum

“…Our hybrid CNN-LSTM-Attention model improves fraud detection by addressing both spatial and temporal data features while dynamically focusing on critical elements. …”
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UAV-based inspection of wind turbine blade surface defects detection technology by TAN Xingguo, ZHANG Gaoming

“…The experimental results show that the detection accuracy of the proposed method for typical blade defects such as trachoma, scratch and crack is above 90%, especially the detection accuracy of crack defects can reach 95%, which verifies the effectiveness and accuracy of the algorithm in blade detection.…”
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Lightweight construction safety behavior detection model based on improved YOLOv8 by Kan Huang, Mideth B. Abisado

“…YOLO (You Only Look Once) is an object detection algorithm that can achieve real-time and efficient object detection by dividing images into grids and predicting the bounding boxes and categories of objects in each grid. …”
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Low-Cost LiDAR Mapping on Bicycles for Urban Road and Sidewalk Detection by T. Bhatia, S. Goel, A. Medury

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NID-DETR: A novel model for accurate target detection in dark environments by Qingyuan Pan, Qiang Liu, Wei Huang

“…Current mainstream algorithms face challenges in extracting meaningful features under low-light conditions, which significantly limits their effectiveness. …”
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SD-YOLO: A Robust and Efficient Object Detector for Aerial Image Detection by Shuaihui Qi, Yi Sun, Xiaofeng Song, Jiting Li, Tongfei Shang, Li Yu

“…Particularly, when deploying detection algorithms on edge computing platforms like uncrewed aerial vehicles (UAVs), it is essential to find out a lightweight network with good trade-off on efficiency and accuracy. …”
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Tea Disease Detection Method Based on Improved YOLOv8 in Complex Background by Junchen Ai, Yadong Li, Shengxiang Gao, Rongsheng Hu, Wengang Che

“…Experimental results show that the proposed YOLO-SSM algorithm has obvious advantages in accuracy and model complexity and can provide reliable theoretical support for efficient and accurate detection and identification of tea leaf diseases in natural scenes.…”
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PCPE-YOLO with a lightweight dynamically reconfigurable backbone for small object detection by Weijia Chen, Jiaming Liu, Tong Liu, Yaoming Zhuang

“…In this paper, we propose PCPE-YOLO, a novel object detection algorithm, specifically designed to address these difficulties. …”
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Research on Underwater Target Detection Technology Based on SMV-YOLOv11n by Dongcheng Liao, Yijun Shen, Jinyu Ou, Yanlian Du

“…To address these issues, this paper proposes an underwater object detection algorithm named SMV-YOLOv11. Firstly, the Swin Transformer is adopted to replace the backbone network, and a novel Multi-scale Spatial and Channel Attention module (MSCA) is designed and integrated into the backbone to enhance its feature extraction capability. …”
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Non-Destructive Detection of Soybean Storage Quality Using Hyperspectral Imaging Technology by Yurong Zhang, Wenliang Wu, Xianqing Zhou, Jun-Hu Cheng

“…The study focused on acquiring raw spectral information using hyperspectral imaging technology, preprocessing by the derivative method (1ST, 2ND), multiplicative scatter correction (MSC), and standard normal variate (SNV). The feature variables were extracted by a variable iterative space shrinkage approach (VISSA), competitive adaptive reweighted sampling (CARS), and a successive projections algorithm (SPA). …”
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Persian SMS Spam Detection using Machine Learning and Deep Learning Techniques by Roya Khorashadizade, Somayyeh Jafarali Jassbi, Alireza Yari

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Tongue Color Analysis and Diseases Detection Based on a Computer Vision System by Abdulghafor Khudhaer Abdullah, Saleem Lateef Mohammed, Ali Al-Naji, Mohammed Sameer Alsabah

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SCoralDet: Efficient real-time underwater soft coral detection with YOLO by Zhaoxuan Lu, Lyuchao Liao, Xingang Xie, Hui Yuan

“…In recent years, climate change and marine pollution have significantly degraded coral reefs, highlighting the urgent need for automated coral detection to monitor marine ecosystems. However, underwater coral detection presents unique challenges, including low image contrast, complex coral structures, and dense coral growth, which limit the effectiveness of general object detection algorithms. …”
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Signals of propaganda-Detecting and estimating political influences in information spread in social networks. by Alon Sela, Omer Neter, Václav Lohr, Petr Cihelka, Fan Wang, Moti Zwilling, John Phillip Sabou, Miloš Ulman

“…Their methods include the use of synchronized or individual bots, multiple accounts operated by one social media management tool, or different manipulations of search engines and social network algorithms, all aiming to promote their ideology. While computational propaganda influences modern society, it is hard to measure or detect it. …”
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An Improved YOLOv9 and Its Applications for Detecting Flexible Circuit Boards Connectors by Gengjie Huang, Yinbing Huang, Haoyang Li, Ziwen Guan, Xuecong Li, Guidong Zhang, Wendong Li, Xiran Zheng

“…Consequently, existing algorithms perform poorly in this task. We improve model YOLOv9 by introducing Multi-scale Dilated Attention (MSDA) on the output side to enhance the ability to capture features, and Deformable Large Kernel Attention (DLKA) on the other side of the output header to improve the ability to adapt to complex defect boundaries. …”
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High-Accuracy Intermittent Strabismus Screening via Wearable Eye-Tracking and AI-Enhanced Ocular Feature Analysis by Zihe Zhao, Hongbei Meng, Shangru Li, Shengbo Wang, Jiaqi Wang, Shuo Gao

“…After these features are processed by the random forest (RF) algorithm, this method experimentally yields 97.1% accuracy in strabismus detection in 70 people under diverse indoor testing conditions, validating the high accuracy and robustness of the method, and implying that the method has strong potential to support widespread and highly accurate strabismus screening.…”
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