Audio copy-move forgery detection with decreasing convolutional kernel neural network and spectrogram fusion by Canghong Shi, Xin Qiu, Min Wu, Xianhua Niu, Xiaojie Li, Sani M. Abdullahi

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Target Detection and Image Enhancement for Underwater Environment: Research on Improving YOLOv7 by Yang Luo, Wen Feng

“…Aiming at the common low accuracy and efficiency problems in underwater target detection, this paper designs an innovative algorithm based on the YOLOv7 framework. …”
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An improved method of AUD-YOLO for surface damage detection of wind turbine blades by Li Zou, Anqi Chen, Xinhua Yang, Yibo Sun

“…Abstract The detection of wind turbine blades (WTBs) damage is crucial for improving power generation efficiency and extending the lifespan of turbines. …”
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FUR-DETR: A Lightweight Detection Model for Fixed-Wing UAV Recovery by Yu Yao, Jun Wu, Yisheng Hao, Zhen Huang, Zixuan Yin, Jiajing Xu, Honglin Chen, Jiahua Pi

“…Even in complex environments with low light, occlusion, or small targets, it can provide more accurate detection results.…”
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Sports video temporal action detection technology based on an improved MSST algorithm by Lai Lixin, Fang Yu

“…Sports videos contain a large number of irrelevant backgrounds and static frames, which affect the efficiency and accuracy of temporal action detection. …”
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BDK-YOLOv8: An Enhanced Algorithm for UAV Infrared Image Object Detection by Nan Xiao, Xianggong Hong, Zixuan Zheng

“…Finally, channel pruning is applied to reduce model parameters and computational complexity, improving detection efficiency.Experimental results show that the proposed algorithm achieves 94.3% mAP50 on the HIT-UAV dataset, a 1.6% improvement over the original YOLOv8n, with a 3% increase in recall. …”
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HGLFNet: Hybrid Global Semantic and Local Detail Feature Network for Lane Detection by Lei Ding, Chunhui Tang, Yi Fang

“…The experimental results comprehensively demonstrate that HGLFNet surpasses the existing state-of-the-art techniques in both accuracy and efficiency, providing a novel and effective solution for lane detection in complex scenarios and showing significant potential in practical applications.…”
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Advancing multi-categorization and segmentation in brain tumors using novel efficient deep learning approaches by Nadenlla RajamohanReddy, G. Muneeswari

“…Brain tumors are most commonly detected by magnetic resonance imaging (MRI) scans. …”
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Self-Supervised Drift-Resilient Classification for Time Series Industrial Anomaly Detection by Myung-Kyo Seo, Byeong Hoon Yoon, Junseung Ryu, Hyung Ju Hwang

“…In modern industrial environments, early detection of anomalies is essential to prevent unplanned downtime and maintain operational efficiency. …”
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Effects of Hybridizing the U-Net Neural Network in Traffic Lane Detection Process by Aron Csato, Florin Mariasiu

“…Similarly, in the Carla dataset (known for the complexity of the generated images), a substantial improvement was recorded, with an increase of +8.0% in mIoU and +5.7% in F1 score, showing better adaptability of the model to geometric structures in complex images. …”
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Research on object detection and recognition in remote sensing images based on YOLOv11 by Lu-hao He, Yong-zhang Zhou, Lei Liu, Wei Cao, Jian-hua Ma

“…Abstract This study applies the YOLOv11 model to train and detect ground object targets in high-resolution remote sensing images, aiming to evaluate its potential in enhancing detection accuracy and efficiency. …”
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Rice disease detection method based on multi-scale dynamic feature fusion by Qian Fan, Runhao Chen, Bin Li

“…In order to enhance the accuracy of rice leaf disease detection in complex farmland environments, and facilitate the deployment of the deep learning model onto mobile terminals for rapid real-time inference, this paper introduces a disease detection network titled YOLOv11 Multi-scale Dynamic Feature Fusion for Rice Disease Detection (YOLOv11-MSDFF-RiceD). …”
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Seedling Stage Corn Line Detection Method Based on Improved YOLOv8 by LI Hongbo, TIAN Xin, RUAN Zhiwen, LIU Shaowen, REN Weiqi, SU Zhongbin, GAO Rui, KONG Qingming

“…However, traditional detection methods struggle to maintain high accuracy and efficiency under challenging conditions, such as strong light exposure and weed interference. …”
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Improved YOLOv8n Models for Object Detection in Remote Sensing Images by Young-Long Chen, Kai-Chun Hung, Jia-Yun Zhang, Ling-Wei Lin

“…However, applying these models to remote sensing images remains challenging due to complex backgrounds, high object scale variation, and the difficulty of detecting small objects. …”
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A policy conflict detection mechanism for multi-controller software-defined networks by You Lu, Qiming Fu, Xuefeng Xi, Zhenping Chen, Encen Zou, Baochuan Fu

“…The experimental results under the campus network environment prove that our method can effectively detect the conflict of flow policies existing in the multi-controller software-defined network and has advantages over the existing methods in the integrity, accuracy, and efficiency of the detection.…”
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Detecting eavesdropping nodes in the power Internet of Things based on Kolmogorov-Arnold networks. by Rong Wang, Weibin Jiang, Yanjin Shen, Qiqing Yue, Kan-Lin Hsiung

“…Traditional eavesdropping detection methods struggle to adapt to complex and dynamic attack patterns, necessitating the exploration of more intelligent and efficient anomaly localization approaches. …”
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Advances in research on novel technologies for the detection of exogenous contaminants in traditional Chinese medicine by Ziyu Guo, Junyao Li, Lina Zeng, Ping Wang, Meifang Li, Chang Su, Shuhong Wang

“…Exogenous contaminants in traditional Chinese medicine (TCM), including pesticide residues, heavy metals, mycotoxins, and sulfur dioxide residues, pose significant risks to human health and environmental safety. Conventional detection methods are limited by insufficient sensitivity, complex sample preparation, and challenges in multi-residue analysis, compromising accuracy and efficiency. …”
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An optimized stacking-based TinyML model for attack detection in IoT networks. by Anshika Sharma, Shalli Rani, Mohammad Shabaz

“…With the expansion of Internet of Things (IoT) devices, security is an important issue as attacks are constantly gaining more complex. Traditional attack detection methods in IoT systems have difficulty being able to process real-time and access limitations. …”
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CP-YOLO: An Algorithm for Cigarette Pack Defects Detection Based on CCD Images by Peng Dong, Weihua Feng, Rui Wang, Mingyan Zhang, Qunye Hong, Yongsheng Wang, Di Wang, Guohao Zong

“…The failure to detect defective packs promptly may affect production efficiency and material consumption. …”
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Indocyanine Green and Arginine-Glycine-Aspartic Acid Complex Used in Intraoperative Visualization during Resection of Bladder Tumour by Li Peng, I. R. Kabirov, A. R. Kasinskaya, Jiaqi Wang, Wanhai Xu, E. K. Zhuk, R. A. Nuralieva

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