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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3L-YOLO: A Lightweight Low-Light Object Detection Algorithm by Zhenqi Han, Zhen Yue, Lizhuang Liu

“…Object detection in low-light conditions presents significant challenges due to issues such as weak contrast, high noise, and blurred boundaries. …”
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Automatic detection of foreign object intrusion along railway tracks based on MACENet. by Xichun Chen, Yu Tian, Ming Li, Bin Lv, Shuo Zhang, Zixian Qu, Jianqing Wu, Shiya Cheng

“…Ensuring high accuracy and efficiency in foreign object intrusion detection along railway lines is critical for guaranteeing railway operational safety under limited resource conditions. …”
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XAIHO: explainable AI leveraging hybrid optimized framework for liver cirrhosis detection by Prashant Kumar Mishra, Brijesh Kumar Chaurasia, Man Mohan Shukla

“…Abstract This study introduces an explainable AI leveraging hybrid optimized framework for liver cirrhosis detection (XAIHO) with deep learning (DL) to address the critical challenges of low interpretability and diagnostic inefficiency in traditional and AI-driven liver cirrhosis detection systems. …”
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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

“…Next, we introduce a Context Anchor Attention mechanism that boosts the model’s focus on the contexts of small objects, thereby improving detection accuracy. In addition, we add a small object detection layer to enhance the model’s localization capability for small objects. …”
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Subsea Nodule Recognition and Deployment Detection Method Based on Improved YOLOv8s by Jixin Li, Junchao Li, Bin Su, Yuxin Cui

“…An improved small-target detection model based on YOLOv8s is proposed to address the challenges associated with deep-sea polymetallic nodule detection, such as complex target shapes, small sizes, and strong environmental interference. …”
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A Proactive Model for Intrusion Detection Using Image Representation of Network Flows by Rimsha Saeed, Hassaan Khaliq Qureshi, Christiana Ioannou, Marios Lestas

“…In addition, an adaptive sliding window technique is introduced for live intrusion detection and prevention. …”
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Small object detection algorithm based on improved YOLOv10 for traffic sign by Yukang Zou, Scarlett Liu

“…Our approach introduces Omni-Dimensional Dynamic Convolution (ODConv), which utilizes a four-dimensional dynamic convolution mechanism to improve the capture of multi-scale and complex background features. Additionally, we integrate an attention-guided bidirectional feature pyramid network (EMA-BiFPN) to enhance feature fusion, further improving the detection accuracy for small objects. …”
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GLS-YOLO: A Lightweight Tea Bud Detection Model in Complex Scenarios by Shanshan Li, Zhe Zhang, Shijun Li

“…To address the demand for high-precision yet lightweight tea bud detection, this study proposes the GLS-YOLO detection model, based on YOLOv8. …”
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YOLO-SRSA: An Improved YOLOv7 Network for the Abnormal Detection of Power Equipment by Wan Zou, Yiping Jiang, Wenlong Liao, Songhai Fan, Yueping Yang, Jin Hou, Hao Tang

“…Power equipment anomaly detection is essential for ensuring the stable operation of power systems. …”
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Harnessing self-supervised learning to boost malicious traffic detection with enhanced attention by SUN Jianwen, ZHANG Bin, LI Hongyu, CHANG Heyu

“…The existing deep learning-based malicious traffic detection methods generally suffered from three main problems: labeled sample scarcity, inadequate representation of malicious behavior traffic features, and a high false positive rate due to ineffective integration of behavioral association patterns during detection. …”
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DEVELOPMENT OF NON-DESTRUCTIVE ROBOT FOR EGGPLANTS (SOLANUM MELONGENA) PEST DETECTION AND CLASSIFICATION by Mark Jayson Y. Sutayco, Eidref Simon Dela Cruz, Harold Aranza, Gian Fernan Collado, Kyle Benedict Lui

“…Effective pest monitoring is essential for farmers to detect potential crop damage, minimize the use of pesticides and insecticides, and optimize harvest yields. …”
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CLINICO PATHOLOGICAL STUDY AND MOLECULAR DETECTION OF IBD INFECTED BROILERS IN BASRAH PROVINCE by Dheyaa abbas abdali, Waleed Majeed Seger Almayahi

“…Various overall changes are observed in the bursa, such as swelling,hemorrhages to atrophy in size; In addition, hemorrhages were seen in the thighmuscles. …”
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Airport Clearance Detection Based on Vision Transformer and Multi-Scale Feature Fusion by Yutong Chen, Yufen Liu, Zhixiong Guo, Qiang Gao

“…Faced with airport complex scenes and small object detection, there are still certain limitations to the traditional object detection algorithm. …”
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Detection of Critical Parts of River Crab Based on Lightweight YOLOv7-SPSD by Guoai Fang, Yu Zhao

“…To enhance the lightweight nature of the YOLOv7-tiny model, we incorporate the Slimneck module, PConv, and the SimAM attention mechanism. These additions help achieve an initial reduction in model size while preserving detection accuracy. …”
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An object detection method in foggy weather based on novel feature enhancement and fusion by ZHU Lei, ZHAO Han, WANG Weili

“…To further improve the detection accuracy of objects in foggy scenes for deep learning networks, a foggy object detection method called NFF-YOLOX is proposed based on the YOLOX network. …”
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Virtual Machine Proactive Fault Tolerance Using Log-Based Anomaly Detection by Pratheek Senevirathne, Samindu Cooray, Jerome Dinal Herath, Dinuni Fernando

“…In this paper, we propose Virtual Machine Proactive Fault Tolerance using Log-based Anomaly Detection (VMFT-LAD), a semi-supervised, real-time log anomaly detection model capable of detecting failures ahead of time to provide effective VM fault tolerance. …”
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Detection of Epstein-Barr virus infection in primary junctional epithelial cell cultures by Lilit Tonoyan, Charles V Olivieri, Marlène Chevalier, Robert Marsault, Alain Doglio

“…JECs and EBV infection of JECs were detected using immunofluorescent staining of cytokeratin 19 and EBNA1, respectively. …”
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Detection and Tracking of MAVs Using a Rosette Scanning Pattern LiDAR by Sandor Gazdag, Tom Moller, Anita Keszler, Andras L. Majdik

“…The presented method utilizes a particle filter with a velocity component for the detection and tracking of the drone, which offers added re-detection capability. …”
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Deep-learning-based detection of underwater fluids in multiple multibeam echosounder data by Tyméa Perret, Gilles Le Chenadec, Arnaud Gaillot, Yoann Ladroit, Stéphanie Dupré

“…The results demonstrate first that this method surpasses current machine learning techniques, such as Haar-Local Binary Pattern Cascade. Additionally, we thoroughly analyzed the composition of the training dataset and evaluated the detection performance based on various training configurations. …”
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