Improving Fire and Smoke Detection with You Only Look Once 11 and Multi-Scale Convolutional Attention by Yuxuan Li, Lisha Nie, Fangrong Zhou, Yun Liu, Haoyu Fu, Nan Chen, Qinling Dai, Leiguang Wang

“…Although challenges remain in handling occluded targets and complex backgrounds, the model exhibits strong robustness and generalization capabilities, maintaining efficient detection performance in complicated environments.…”
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TCCDNet: A Multimodal Pedestrian Detection Network Integrating Cross-Modal Complementarity with Deep Feature Fusion by Shipeng Han, Chaowen Chai, Min Hu, Yanni Wang, Teng Jiao, Jianqi Wang, Hao Lv

“…Multimodal pedestrian detection has garnered significant attention due to its potential applications in complex scenarios. …”
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Vision transformer-enhanced thermal anomaly detection in building facades through fusion of thermal and visible imagery by Siyu Zheng, Jiaxin Zhang, Rui Zu, Yunqin Li

“…The experimental outcomes reveal that our methodology, with an F1 score of 0.847, markedly surpasses traditional thermal imaging (F1 score of 0.466), showcasing its potential for precise anomaly detection in architectural contexts. This validates the method as a more robust and efficient solution for structural evaluation, promising to elevate the quality of architectural inspections and maintenance.…”
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A novel approach to intrusion detection system using hybrid flower pollination and cheetah optimization algorithm by Deepshikha Kumari, Prashant Pranav, Abhinav Sinha, Sandip Dutta

“…Key performance metrics were analysed to assess the model’s effectiveness in detecting malicious activities in complex network traffic patterns. …”
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DAM-Faster RCNN: few-shot defect detection method for wood based on dual attention mechanism by Xingyu Tong, Zhihong Liang, Mingming Qin, Fangrong Liu, Jiayu Yang, Hengjiang Xiao, Wei Dai

“…Experimental results show that the proposed method achieves state-of-the-art performance on the PASCAL VOC and FSOD datasets, particularly in the identification of 17 types of wood defects, where AP50 and AP75 are improved by 25% and 7.9%, respectively, validating the significant advantages of the proposed DAM mechanism under few-shot and complex background conditions. The findings of this study provide practical technical references for intelligent and efficient few-shot detection in real-world wood quality inspection tasks.…”
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Analysis of VAE-LSTM Performance in Detecting Anomalies in Average Daily Temperature Data in Jakarta 2000-2023 by INDRI RAMDANI, YENNI ANGRAINI, INDAHWATI INDAHWATI

“…This study contributes to climate research by providing evidence of the effectiveness of deep learning-based hybrid models in detecting complex and context-sensitive temperature anomalies.…”
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Real-time Detection Algorithm of Expanded Feed Image on the Water Surface Based on Improved YOLOv11 by ZHOU Xiushan, WEN Luting, JIE Baifei, ZHENG Haifeng, WU Qiqi, LI Kene, LIANG Junneng, LI Yijian, WEN Jiayan, JIANG Linyuan

“…These improvements showed the effectiveness of the YOLOv11-AP2S model in detecting floating extruded feed particles in complex environments. …”
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WTDBNet: A Wavelet Transform-Based Dual-Stream Backbone Network for Fine-Grained Ship Detection by Wei Cao, Xinyu Zhao, Hongqi Wang, Yuxin Hu

“…Fine-grained ship detection tasks require models to accurately classify fine-grained categories and precisely localize them within complex backgrounds, relying on detailed features. …”
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Anomaly Detection of Pipeline Leakage Based on Electric Field Component Imaging Using Ground Penetrating Radar by Yang Yang, Zhiyuan Du, Yanan Li, Tianyu Zhang, Lu Liu, Ibrar Iqbal, Sanxi Peng

“…Ground penetrating radar (GPR) is an effective method that can be applied in pipeline leakage detection. However, when the distribution of the underground medium is complex, it becomes difficult to accurately identify the abnormal leakage area directly from the GPR data profile. …”
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DDoSNet: Detection and prediction of DDoS attacks from realistic multidimensional dataset in IoT network environment by Goda Srinivasa Rao, P. Santosh Kumar Patra, V.A. Narayana, Avala Raji Reddy, G.N.V. Vibhav Reddy, D. Eshwar

“…The Internet of Things (IoT) network infrastructures are becoming more susceptible to distributed denial of service (DDoS) attacks because of the proliferation of IoT devices. Detecting and predicting such attacks in this complex and dynamic environment requires specialized techniques. …”
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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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Research on Concrete Crack and Depression Detection Method Based on Multi-Level Defect Fusion Segmentation Network by Zhaochen Yao, Yanjuan Li, Hao Fu, Jun Tian, Yang Zhou, Chee-Loong Chin, Chau-Khun Ma

“…Joint detection loss and segmentation loss are used for task co-optimization. …”
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DMS-OGSTV: A Novel Infrared Small Target Detection Based on Spatial-Temporal Tensor Model by Xiaoling Ge, Weixian Qian, Zipeng Fu

“…Detecting small targets in complex infrared backgrounds is challenging due to edge aliasing and noise interference. …”
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Target detection technology of coal mine wheeled robot combining improved CNN and self attention mechanism by Junfei TANG, Hailong XING, Su LI, Taotao ZHANG, Heng LIU, Shiyu YAO

“…The accuracy of the model reached 0.95 at 1 598 iterations and entered steady state at about 1 845 iterations, which was one of the fastest models to reach steady state. The overall detection time was 3.2 ms. The model can improve the accuracy and efficiency of target detection in complex environment.…”
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ADAM-DETR: an intelligent rice disease detection method based on adaptive multi-scale feature fusion by Hanyu Song, Xinyue Huang, Ziqiang Wang, Jianwei Hu, Huasheng Zhang, Hui Yang

“…Abstract Rice diseases pose a severe threat to global food security, while traditional detection methods suffer from low efficiency and dependence on manual expertise. …”
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VAE-Based Real-Time Anomaly Detection Approach for Enhanced V2X Communication Security by Yonas Teweldemedhin Gebrezgiher, Sekione Reward Jeremiah, Stefanos Gritzalis, Jong Hyuk Park

“…By delivering high performance, adaptability, and efficiency, our method provides a reliable way to detect and prevent cyberattacks, thereby making intelligent transportation systems safer and more dependable.…”
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Edge Computing-Based Real-Time Forest Fire Detection Using UAV Thermal and Color Images by Lingxia Mu, Yichi Yang, Ban Wang, Youmin Zhang, Nan Feng, Xuesong Xie

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Trace level detection of Pb2+ ion using organic ligand as fluorescent-on probes in aqueous media by Maria Sadia, Jehangir Khan, Rizwan Khan, Syed Wadood Ali Shah, Adil Zada, Muhammad Zahoor, Riaz Ullah, Essam A. Ali

“…The sensor exhibited high efficiency and selectivity in detecting Pb2+ ions, even in the presence of potential interfering ions such as Mn2+, Cu2+, Co2+, Cr3+, Ni2+, Ce3+, Hg2+, and Cd2+ in aqueous solutions. …”
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Knowledge distillation-enhanced marine optical remote sensing object detection with transformer and dual-path architecture by Yubin Yuan, Yiquan Wu, Langyue Zhao, Yuqi Liu, Jinlin Chen

“…Furthermore, the framework incorporates a Multivariate Matching strategy with Gaussian spatial constraints to improve anchor-object correspondence in complex marine scenarios. To balance detection accuracy with computational efficiency, a knowledge distillation framework is implemented where a compact student model learns distilled representations through multi-granularity alignment with a teacher network, encompassing intermediate feature guidance and output-level probability calibration. …”
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STar-DETR: A Lightweight Real-Time Detection Transformer for Space Targets in Optical Sensor Systems by Yao Xiao, Yang Guo, Qinghao Pang, Xu Yang, Zhengxu Zhao, Xianlong Yin

“…Optical sensor systems are essential for space target detection. However, previous studies have prioritized detection accuracy over model efficiency, limiting their deployment on resource-constrained sensors. …”
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