D³-YOLOv10: Improved YOLOv10-Based Lightweight Tomato Detection Algorithm Under Facility Scenario by Ao Li, Chunrui Wang, Tongtong Ji, Qiyang Wang, Tianxue Zhang

“…Accurate and efficient tomato detection is one of the key techniques for intelligent automatic picking in the area of precision agriculture. …”
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Acoustic emission localization model of concrete material based on convolutional neural network by DENG Yongdong, ZHOU Jingren, LU Xiang, CHEN Jiangkang

“…The damage location detected by the localization model basically matches the real crack location.ConclusionsThe proposed localization model shows good localization efficiency and localization accuracy. …”
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LMSOE-Net: lightweight multi-scale small object enhancement network for UAV aerial images by Zhixing Ma, Peidong Luo, Xiaole Shen

“…To tackle this issue, we propose a lightweight multi-scale small object enhancement network (LMSOE-Net) based on the YOLOv8 architecture. To improve both detection performance and model efficiency, we introduce the Efficient Multi Scale Pyramid (EMSP) neck network. …”
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Near-real-time wildfire detection approach with Himawari-8/9 geostationary satellite data integrating multi-scale spatial–temporal feature by Lizhi Zhang, Qiang Zhang, Qianqian Yang, Linwei Yue, Jiang He, Xianyu Jin, Qiangqiang Yuan

“…To address this, we propose a deep learning model for near-real-time wildfire detection, where the core idea is to integrate multi-scale spatial–temporal features (MSSTF) to efficiently capture the dynamics of wildfires. …”
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Evaluation of classification algorithms in the Google Earth Engine platform for the identification and change detection of rural and periurban buildings from very high-resolution i... by Alejandro Coca-Castro, Maycol A. Zaraza-Aguilera, Yilsey T. Benavides-Miranda, Yeimy M. Montilla-Montilla, Heidy B. Posada-Fandiño, Angie L. Avendaño-Gomez, Hernando A. Hernández-Hamon, Sonia C. Garzón-Martinez, Carlos A. Franco-Prieto

“…Building change detection based on remote sensing imagery is a key task for land management and planning e.g., detection of illegal settlements, updating land records and disaster response. …”
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A Lightweight Person Detector for Surveillance Footage Based on YOLOv8n by Qicheng Wang, Guoqiang Feng, Zongzhe Li

“…To enable person detection tasks in surveillance footage to be deployed on edge devices and their efficient performance in resource-constrained environments in real-time, a lightweight person detection model based on YOLOv8n was proposed. …”
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A recognition model for winter peach fruits based on improved ResNet and multi-scale feature fusion by Yan Li, Chunping Li, Tingting Zhu, Shurong Zhang, Li Liu, Zhanpeng Guan

“…The GhostConv module further improves detection accuracy by reducing the number of convolution kernels. …”
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StApneaNet: A Deep Learning-Based Automatic Sleep Stage Adaptive Apnea Detection Network Using Single Channel EEG Signal by Suvasish Saha, Shaikh Anowarul Fattah, Mohammad Saquib

“…Both apnea prediction and sleep stage prediction are jointly optimized in the joint model that is initially pre-trained and later integrated as a non-trainable block with the trainable decision fusion block inside the decision model for the final apnea event detection. The whole trained network so built is capable of efficiently predicting apnea frames in the testing phase. …”
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Historical Blurry Video-Based Face Recognition by Lujun Zhai, Suxia Cui, Yonghui Wang, Song Wang, Jun Zhou, Greg Wilsbacher

“…Historical motion picture films often have poorer resolution than modern digital imagery, making face detection a more challenging task. To approach this problem, we first propose a trunk–branch concatenated multi-task cascaded convolutional neural network (TB-MTCNN), which efficiently extracts facial features from blurry historical films by combining the trunk with branch networks and employing various sizes of kernels to enrich the multi-scale receptive field. …”
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Evaluating sowing uniformity in hybrid rice using image processing and the OEW-YOLOv8n network by Zehua Li, Zehua Li, Yihui Pan, Xu Ma, Yongjun Lin, Xicheng Wang, Hongwei Li

“…This improvement can enhance the feature extraction ability of the Backbone network, as the new modules can fully utilize the information of all dimensions of the convolutional kernel. (2) An Efficient Channel Attention (ECA) module is added to the Neck for improving the network’s capability to extract deep semantic feature information of the detection target. (3) In the Bbox module of the prediction head, the Complete Intersection over Union (CIoU) loss function is replaced by the Weighted Intersection over Union version 3 (WIoUv3) loss function to improve the convergence speed of the bounding box loss function and reduce the convergence value of the loss function. …”
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Power Equipment Image Recognition Method Based on Feature Extraction and Deep Learning by Shuang Lin

“…This paper proposes an improved attention mechanism-based network for image detection and recognition of power equipment. The proposed method introduces a target feature prediction strategy tailored to power equipment: it incorporates a learning mechanism for depth variation to extract deep semantic information from images; enhances the global structure learning network module by stacking convolutional kernels and removing pooling layers in the front-end network, thereby acquiring prior information rich in detailed and correlated image features of power equipment. …”
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YOLOv9-LSBN: An Improved YOLOv9 Model for Cotton Pest and Disease by Ruohong He, Fengkui Zhang, Jikui Zhu, Yulong Wang, Daorina Yang, Ting Zhang, Ping Li

“…To achieve accurate identification of cotton aphids and diseases in natural complex environments, an enhanced YOLOv9 model named YOLOv9-LSBN (Large Selective Kernel Network with Bidirectional Feature Pyramid) is proposed. …”
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Study and implementation of integrated network security monitoring system by ZHANG Hui-min, QIAN Yi-ping, ZHENG Qing-hua, DONG Shi-jie, GUAN Xiao-hong

“…In this paper, we present the framework of NSMS, and then discuss some key issues of implementation, which are proof-getting, 損roof-correlation and result-visualization respectively. As the kernel of integrated network security and defense system, the prototype of NSMS has already been developed and tested, it is proved to be efficient, open and practical in network security monitoring.…”
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Optimal features assisted multi-attention fusion for robust fire recognition in adverse conditions by Inam Ullah, Nada Alzaben, Yousef Ibrahim Daradkeh, Mi Young Lee

“…Extensive comparisons against twelve SOTA approaches confirm AEFRN’s effectiveness for fire detection in challenging scenarios while maintaining computational efficiency suitable for practical deployment.…”
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MCRS-YOLO: Multi-Aggregation Cross-Scale Feature Fusion Object Detector for Remote Sensing Images by Lu Liu, Jun Li

“…Compared with the baseline YOLOv11, the proposed method demonstrates improvements of 4.0% and 6.7% in mean Average Precision (mAP), which provides an efficient and accurate solution for object detection in remote sensing images.…”
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Attention-driven hybrid deep learning and SVM model for early Alzheimer’s diagnosis using neuroimaging fusion by Arjun Kidavunil Paduvilan, Godlin Atlas Lawrence Livingston, Sampath Kumar Kuppuchamy, Rajesh Kumar Dhanaraj, Muthuvel Subramanian, Amal Al-Rasheed, Masresha Getahun, Ben Othman Soufiene

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Research on Identification of Soft-Fault Level in VRF System Based on Classifier Chain by He Yuxuan, Shi Jingfeng, Zhou Zhenxin, Chen Huanxin, Ren Zhaoting, Xia Xingxiang, Cheng Hengda

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Infrared Thermography-Based Insulator Fault Classification via Unsupervised Clustering and Semi-Supervised Learning by Usman Shafique, Syed Muhammad Alam, Umar Rashid, Wahab Javed, Haris Anwaar, Malik Shah Zeb, Talha Ahmad, Uzair Imtiaz, Frederic Nzanywayingoma

“…This paper addresses the critical issue of insulator fault detection in electric substations, emphasizing the importance of timely identification to prevent accidents. …”
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Enhancing Security in Industrial IoT Networks: Machine Learning Solutions for Feature Selection and Reduction by Ahmad Houkan, Ashwin Kumar Sahoo, Sarada Prasad Gochhayat, Prabodh Kumar Sahoo, Haipeng Liu, Syed Ghufran Khalid, Prince Jain

“…By comparing these methods, it showcases their influence on both model performance and complexity, leading to the development of more efficient and precise intrusion detection systems for Industrial IoT networks. …”
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High-Precision Pose Measurement of Containers on the Transfer Platform of the Dual-Trolley Quayside Container Crane Based on Machine Vision by Jiaqi Wang, Mengjie He, Yujie Zhang, Zhiwei Zhang, Octavian Postolache, Chao Mi

“…A multi-scale adaptive frequency object-detection framework is developed based on YOLO11, achieving improved detection accuracy for multi-scale lockhole keypoints in perspective-distortion scenarios (mAP@0.5 reaches 95.1%, 4.7% higher than baseline models) through dynamic balancing of high–low-frequency features and adaptive convolution kernel adjustments. …”
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