Polarimetric SAR Ship Detection Using Context Aggregation Network Enhanced by Local and Edge Component Characteristics by Canbin Hu, Hongyun Chen, Xiaokun Sun, Fei Ma

“…However, polarization SAR methods for ship detection still face challenges. The traditional constant false alarm rate (CFAR) detectors face sea clutter modeling and parameter estimation problems in ship detection, which is difficult to adapt to the complex background. …”
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DCN-YOLO: A Small-Object Detection Paradigm for Remote Sensing Imagery Leveraging Dilated Convolutional Networks by Meilin Xie, Qiang Tang, Yuan Tian, Xubin Feng, Heng Shi, Wei Hao

“…To address this problem, we propose to use multi-scale dilated convolutions to increase the receptive field size of the model to adapt to changes in object size, capture multi-scale contextual information of the feature map, and extract richer object features. …”
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Detecting Anomalies in CPU Behavior Using Clustering Algorithms from the Scikit-Learn Library in Python Programming Language by Artem Turashev, Vladimir Sukhomlin

“…This article examines the problem of detecting anomalies in central processing unit (CPU) operation using time series clustering algorithms. …”
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A UAV-Based Multi-Scenario RGB-Thermal Dataset and Fusion Model for Enhanced Forest Fire Detection by Yalin Zhang, Xue Rui, Weiguo Song

“…A time-synchronized multi-scene, multi-angle aerial RGB-Thermal dataset (RGBT-3M) with “Smoke–Fire–Person” annotations and modal alignment via the M-RIFT method was constructed as a way to address the problem of data scarcity in wildfire scenarios. Finally, we propose a CP-YOLOv11-MF fusion detection model based on the advanced YOLOv11 framework, which can learn heterogeneous features complementary to each modality in a progressive manner. …”
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A Study on Surface Anomaly Detection for Metro Vehicle Underbody Parts Based on 3D Point Cloud by PENG Liantie, LI Chen, XIONG Minjun, YAN Jiayun, CUI Xiaoyang, LIU Leixinyuan

“…This can help reflect the surface features of components more precisely and contribute to accurate anomaly detection. …”
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A Hybrid Attention Mechanism and RepGFPN Method for Detecting Wall Cracks in High-Altitude Cleaning Robots by Haiqiao Liu, Lingding Li, Ya Li, Qing Long, Zhuoyu Chen

“…Aiming at the problem that cracks with different shapes and scales on the exterior walls of high buildings are difficult to detect, this paper proposed a wall crack detection method for high-altitude cleaning robots by hybridizing the GAM attention mechanism and RepGFPN. …”
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Android malware detection via efficient application programming interface call sequences extraction and machine learning classifiers by Tanjie Wang, Yueshen Xu, Xinkui Zhao, Zhiping Jiang, Rui Li

“…We generate the transition matrix as classification features and investigate three types of machine learning classifiers to complete the malware detection task. …”
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Audio recognition method of belt conveyor roller fault based on convolutional neural network and linear regression by Xiangyuan CHEN, Wei QIN, Yanchi LIU, Minghua LUO

“…The results show that the detection rate of roller fault reaches 95.79 %, and the detection accuracy reaches 95.60 %.…”
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Detection of Melamine in Soybean Meal Using Near-Infrared Microscopy Imaging with Pure Component Spectra as the Evaluation Criteria by Zengling Yang, Lujia Han, Chengte Wang, Jing Li, Juan A. Fernández Pierna, Pierre Dardenne, Vincent Baeten

“…NIR microscopy imaging offers the opportunity to investigate the chemical species present in food and feed at the microscale level (the minimum spot size is a few micrometers), thus avoiding the problem of the spectral features of contaminants being diluted by scanning. …”
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The Detection of Fake Text News using a Dense-based 1D-CNN Deep Learning Algorithm by Khalid Abood Kamel, Jumana Waleed

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DSCW-YOLO: Vehicle Detection from Low-Altitude UAV Perspective via Coordinate Awareness and Collaborative Module Optimization by Qingqi Zhang, Hao Wang, Xinbo Wang, Jiapeng Shang, Xiaoli Wang, Jie Li, Yan Wang

“…This paper proposes an optimized algorithm based on YOLOv11s to address the problem of insufficient detection accuracy of vehicle targets from a drone perspective due to certain scenes involving complex backgrounds, dense vehicle targets, and/or large variations in vehicle target scales due to oblique imaging. …”
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Automatic Detection and Classification of Natural Weld Defects Using Alternating Magneto-Optical Imaging and ResNet50 by Yanfeng Li, Pengyu Gao, Yongbiao Luo, Xianghan Luo, Chunmei Xu, Jiecheng Chen, Yanxi Zhang, Genxiang Lin, Wei Xu

“…It is difficult to detect and identify natural defects in welded components. …”
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FaultVitNet: A Vision Transformer Assisted Network for 3D Fault Segmentation by Chao Li, Sergey Fomel, Yangkang Chen, Robin Dommisse, Alexandros Savvaidis

“…However, due to the limited receptive field of the convolutional neural network (CNN), CNN will inherently pay more attention to local information, causing the risk of destroying the global completeness of faults and degrading fault detection accuracy. To overcome this problem, we propose an improved vision transformer and incorporate it into classic CNN to strengthen its ability for complex fault detection. …”
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A hybrid CNN-BILSTM deep learning framework for signal detection of a massive MIMONOMA system by Mohamed A. Abdelhamed, Mennatalla Samy, Bassem E. Elnaghi, Ahmed Magdy

“…Deep learning (DL) signal detection methods solve this problem. In the proposed hybrid model, a convolutional neural network (CNN) and bidirectional feed-forward recurrent neural networks (RNNs) are combined to improve error optimization. …”
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MATHEMATICAL MODEL FOR SEARCHING AND DETECTING EXPLOSIVE DEVICES WITH NON-CONTACT TARGET SENSORS BY THE METHOD OF NON-LINEAR RADAR by Oleksandr Smolkov, Volodymyr Kotsiuruba, Konstantin Hunbin

“…These features are the basis of modern means of detecting explosive devices with non-contact target sensors by nonlinear radar. …”
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HD-MVCNN: High-density ECG signal based diabetic prediction and classification using multi-view convolutional neural network by D. Santhakumar, K. Dhana Shree, M. Buvanesvari, A. Saran Kumar, Ayodeji Olalekan Salau

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A multi-factor integration-based semi-supervised learning for address resolution protocol attack detection in SDIIoT by Zhong Li, Huimin Zhuang

“…These advantages prompt us to propose a multi-factor integration-based semi-supervised learning address resolution protocol detection method deployed in software-defined networking, called MIS, to specially solve the problems of limited labeled training data and incomplete features extraction in the traditional address resolution protocol detection methods. …”
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YOLO-RDM: A high accuracy and efficient algorithm for magnetic tile surface defect detection with practical applications. by Wei Niu, Cheng Lv, Enxu Zhang, Zhongbin Wei

“…To solve these problems, this study proposes a novel magnetic tile defect detection algorithm called YOLO-RDM. …”
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Personalized Solutions for Foot Health: Machine Learning-Based Foot Condition Detection, Classification, and Recommendation of Customized Footwear by Sonaa Rajagopal, Muralikrishnan Mani, Shyam Venkatraman, R. Suganya

“…The framework consists of three modules: a CNN-based VGG-16-GRU model which identifies gait posture based on pressure sensor heatmaps, an autoencoder-based random forest model which classifies foot diseases based on the detected gait posture, and an LSTM-ensembled XGBoost model which recommends features of suggested footwear. …”
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Epidemic situation and features of accompanying therapy in the treatment of socially significant infectious diseases in penitentiary populations before, during, and after the COVID... by V. M. Kolomiets, N. A. Polshikova, A. Yu. Petrov, A. L. Kovalenko, E. V. Talikova

“…Moreover, all cases were detected in pre-trial detention centers when detainees were admitted to them; these diseases were not recorded in correctional facilities. …”
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