DAHD-YOLO: A New High Robustness and Real-Time Method for Smoking Detection by Jianfei Zhang, Chengwei Jiang

“…However, the existing smoking behavior detection models based on object detection still have problems, including poor accuracy and insufficient real-time performance. …”
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A Lightweight Pavement Defect Detection Algorithm Integrating Perception Enhancement and Feature Optimization by Xiang Zhang, Xiaopeng Wang, Zhuorang Yang

“…In addition, a shared detail-enhanced convolution lightweight detection head (SDCLD) was designed, which significantly reduces the model’s parameters and computation while improving localization and classification performance. …”
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GESC-YOLO: Improved Lightweight Printed Circuit Board Defect Detection Based Algorithm by Xiangqiang Kong, Guangmin Liu, Yanchen Gao

“…Finally, the coordinate attention is introduced into the neck network to decompose the channel attention and aggregate the features, which can effectively retain the spatial information and thus improve the detection and localization accuracy of tiny defects (defect area less than 1% of total image area) in PCB defect images. …”
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Detection and classification of breast cancer in mammographic images with fine-tuned convolutional neural networks by Huong Hoang Luong, Hai Thanh Nguyen, Nguyen Thai-Nghe

“…This study proposed a procedure to fine-tune the Convolutional Neural Networks (CNN) model with data preprocessing and augmentation in classifying mammogram images called the Hybrid Mammogram Classification and Detection Pipeline (HMCaD). After using CNN for classification because it brings higher confidence in classifying tasks, the YOLOv8 has been applied for localization subtask to detect abnormal positions with predicted bounding boxes. …”
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Optimized PCF architectures for THz detection of aquatic pathogens: Enhancing water quality monitoring. by Diponkar Kundu, Nasir Uddin Badhon, A H M Iftekharul Ferdous, Md Safiul Islam, Md Galib Hasan, Khalid Sifulla Noor, Most Momtahina Bani

“…These improvements improve the sensor's trace bacteria detection. These factors increase the sensor's aquatic germ detection when combined. …”
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Defect Detection of Gas Insulation Switch by Infrared Thermography Technology With an Improved Yolo Algorithm by Ma Tianci, Chen Xiangping, Li Bo, Bai Jie

“…To address those issues, this study has proposed an infrared thermography-based defect detection method by combing with an enhanced YOLOv7 algorithm for accurate and efficient defect localization identification and depth estimation. …”
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Vision Gaze-Driven Micro-Electro-Mechanical Systems Light Detection and Ranging Optimization by Shaotang Wei, Bo Gao, Junya Wang, Zheng You

“…Micro-electro-mechanical systems (MEMS) light detection and ranging (LiDAR) systems are widely employed in diverse applications for their precise ranging and high-resolution imaging capabilities. …”
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Feasibility of EfficientDet-D3 for Accurate and Efficient Void Detection in GPR Images by Sung-Pil Shin, Sang-Yum Lee, Tri Ho Minh Le

“…The detection of voids in pavement infrastructure is essential for road safety and efficient maintenance. …”
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Fast Identification and Detection Algorithm for Maneuverable Unmanned Aircraft Based on Multimodal Data Fusion by Tian Luan, Shixiong Zhou, Yicheng Zhang, Weijun Pan

“…To address the critical challenges of insufficient monitoring capabilities and vulnerable defense systems against drones in regional airports, this study proposes a multi-source data fusion framework for rapid UAV detection. Building upon the YOLO v11 architecture, we develop an enhanced model incorporating four key innovations: (1) A dual-path RGB-IR fusion architecture that exploits complementary multi-modal data; (2) C3k2-DATB dynamic attention modules for enhanced feature extraction and semantic perception; (3) A bilevel routing attention mechanism with agent queries (BRSA) for precise target localization; (4) A semantic-detail injection (SDI) module coupled with windmill-shaped convolutional detection heads (PCHead) and Wasserstein Distance loss to expand receptive fields and accelerate convergence. …”
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YOLO in Healthcare: A Comprehensive Review of Detection Architectures, Domain Applications, and Future Innovations by Damodharan Palaniappan, Rituraj Jain, T. Premavathi, Kumar Parmar, Wade Ghribi, Abdelmoty M. Ahmed, Naim Ahmad

“…Across oncology, radiology, pathology, surgery, and PPE detection, YOLO models have demonstrated strong performance in tumor localization, lesion segmentation, tool tracking, and anomaly detection. …”
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ASCDet: cross-space UAV object detection method guided by adaptive sparse convolution by Gui Cheng, Xubin Feng, Yan Tian, Meilin Xie, Chaoya Dang, Qing Ding, Zhenfeng Shao

“…The method utilizes an adaptive pixel-level mask unit based on a task-alignment strategy to accurately localize object regions. These masks guide cross-space object detection through sparse convolutions, while a global context enhancement strategy within the sparse convolution module enriches the contextual information, maintaining detection accuracy. …”
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Development of ANPR Framework for Pakistani Vehicle Number Plates Using Object Detection and OCR by Salma, Maham Saeed, Rauf ur Rahim, Muhammad Gufran Khan, Adil Zulfiqar, Muhammad Tahir Bhatti

“…The proposed framework localizes the number plate region using the YOLO (You Only Look Once) object detection model, applies robust preprocessing techniques on the extracted plate region, and finally recognizes the plate label using OCR (optical character recognition) Tesseract. …”
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STAR-YOLO: A High-Accuracy and Ultra-Lightweight Method for Brain Tumor Detection by Liyan Sun, Linxuan Zheng, Zhiguo Xiao, Yi Xin, Linqing Jiang

“…Brain tumors are among the deadliest malignant neoplasms worldwide, and early detection is critical for improving treatment outcomes and patient prognosis. …”
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Efficient tuna detection and counting with improved YOLOv8 and ByteTrack in pelagic fisheries by Yuanchen Cheng, Zichen Zhang, Yuqing Liu, Jie Li, Zhou Fu

“…Additionally, a dynamic, task-aligned detection head is introduced to optimize the synergy between classification and localization tasks. …”
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MMYFnet: Multi-Modality YOLO Fusion Network for Object Detection in Remote Sensing Images by Huinan Guo, Congying Sun, Jing Zhang, Wuxia Zhang, Nengshuang Zhang

“…Object detection in remote sensing images is crucial for airport management, hazard prevention, traffic monitoring, and more. …”
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Research on Breast Cancer Detection Methods Based on ODMV-MulDyHead-YOLO by Yanhong Zhang, Pei Li, Yihua Lan, Xiao Jia, Yingjie Lv

“…Finally, a loss function based on the minimum point distance is used to improve target localization accuracy and convergence speed. The experimental results show that the improved model achieves higher accuracy, sensitivity, and detection speed than previous models, and reduces false positive and false negative rates. …”
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Convolutional neural network approach for fault detection and characterization in medium voltage distribution networks by Atefeh Pour Shafei, J.Fernando A. Silva, J. Monteiro

“…However, recent advances in artificial intelligence (AI) are enabling researchers to create alternative approaches for fault detection and location strategies. Therefore, this paper introduces a novel method for detecting, classifying, and locating faults in power systems through voltage waveform analysis using a convolutional neural network (CNN) integrated with the Piecewise Function Put Together (PFPT) algorithm for fault detection and fault zone localization in a power distribution network. …”
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DSNet enables feature fusion and detail restoration for accurate object detection in foggy conditions by Zhiyong Jing, Zhaobing Chen, Yucheng Shi, Lei Shi, Lin Wei, Yufei Gao

“…Abstract In real-world scenarios, adverse weather conditions can significantly degrade the performance of deep learning-based object detection models. Specifically, fog reduces visibility, complicating feature extraction and leading to detail loss, which impairs object localization and classification. …”
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USD-YOLO: An Enhanced YOLO Algorithm for Small Object Detection in Unmanned Systems Perception by Hongqiang Deng, Shuzhe Zhang, Xiaodong Wang, Tianxin Han, Yun Ye

“…To address these issues, we propose a specialized algorithm named Unmanned-system Small-object Detection-You Only Look Once (USD-YOLO). First, we designed an innovative module called the Anchor-Free Precision Enhancer to achieve more accurate bounding box overlap measurements and provide a smarter processing mechanism, thereby improving the localization accuracy of candidate boxes for small and densely distributed objects. …”
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FedDB: A Federated Learning Approach Using DBSCAN for DDoS Attack Detection by Yi-Chen Lee, Wei-Che Chien, Yao-Chung Chang

“…In this research, we propose personalized federated learning (PFL) as a solution for detecting DDoS attacks. PFL preserves data privacy by keeping sensitive information localized on individual devices during model training, thus addressing privacy concerns that are inherent in traditional approaches. …”
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