Identification and characterization of near surface cavities in Tuwaiq Mountain Limestone, Riyadh, KSA, “detection and treatment” by Ahmed Abd El Aal

“…The karst features such as fill cavity, boulder, pinnacle, discontinuity and overhang were detected in the survey lines. …”
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Ocean Target Electric Field Signal Analysis and Detection Using LOFAR Based on Basis Pursuit by Huiwen Hu, Xuepeng Sun, Guocheng Wang, Lintao Liu

“…An ocean target electric field signal is an effective approach for analyzing the ocean environment and is widely used for detecting ocean targets, extracting their features, and tracking them. …”
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Beyond conventional vision: RGB-event fusion for robust object detection in dynamic traffic scenarios by Zhanwen Liu, Yujing Sun, Yang Wang, Nan Yang, Shengbo Eben Li, Xiangmo Zhao

“…This deficiency hinders the extraction of discriminative features and degrades the performance of frame-based traffic object detection. …”
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LBT-YOLO: A Lightweight Road Targeting Algorithm Based on Task Aligned Dynamic Detection Heads by Pei Tang, Zhenyu Ding, Minnan Jiang, Weikai Xu, Mao Lv

“…This detection head reduces the number of parameters by sharing the neck network features, and performs task decomposition alignment to achieve high accuracy target detection using dynamic convolution and dynamic feature selection. …”
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A novel dual-student reverse knowledge distillation method for magnetic tile defect detection by Jiyan Tang, Ao Zhang, Weian Liu

“…Abstract Magnetic tiles surface defect detection is crucial in industrial production. However, it is difficult to effectively detect and locate defective areas in magnetic tiles due to the following problems: (1) The defect texture of the magnetic tile material is highly similar to the background texture; (2) The image contrast between the normal and defective areas of the magnetic tile is low; (3) The size and morphology of the defects of the magnetic tile vary greatly. …”
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Intrusion Detection in IoT Networks Using Dynamic Graph Modeling and Graph-Based Neural Networks by William Villegas-Ch, Jaime Govea, Alexandra Maldonado Navarro, Pablo Palacios Jativa

“…To address this problem, this study proposes a graph-based intrusion detection model using Graph Neural Networks (GNNs), leveraging a dynamic representation of IoT network traffic. …”
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Investigation of an Efficient Multi-Class Cotton Leaf Disease Detection Algorithm That Leverages YOLOv11 by Fangyu Hu, Mairheba Abula, Di Wang, Xuan Li, Ning Yan, Qu Xie, Xuedong Zhang

“…Cotton leaf diseases can lead to substantial yield losses and economic burdens. Traditional detection methods are challenged by low accuracy and high labor costs. …”
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Distributed Denial of Service Attack Detection in Software-Defined Networks Using Decision Tree Algorithms by Ali Zaman, Salman A. Khan, Nazeeruddin Mohammad, Abdelhamied A. Ateya, Sadique Ahmad, Mohammed A. ElAffendi

“…The study finds that a decision tree constructed with a hill climbing approach, termed the greedy decision tree, iteratively adds features on the basis of model performance and provides a simpler and more effective strategy for the detection of DDoS attacks in SDNs when compared with recently proposed schemes in the literature. …”
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A Blockchain-Based Federated Forest for SDN-Enabled In-Vehicle Network Intrusion Detection System by Ibrahim Aliyu, Marco Carlo Feliciano, Selinde Van Engelenburg, Dong Ok Kim, Chang Gyoon Lim

“…Using Fourier transform, we decomposed the CAN IDs cycle from CAN bus traffic in the frequency domain for better generalization in multiclass detection of attacks. Multiple statistical and entropy features were extracted to handle the high complexity and non-linearity in CAN bus traffic. …”
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MAVM-UNet: multiscale aggregated vision MambaU-Net for field rice pest detection by Congqi Zhang, Ting Zhang, Guanyu Shang

“…Pests in rice fields not only affect the yield and quality of rice but also cause serious ecological and environmental problems due to the heavy reliance on pesticides. Since various pests have irregular and changeable shapes, small sizes, and complex backgrounds, field rice pest detection is an essential prerequisite and challenge for the precise control of pests in the field. …”
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ZZ-YOLOv11: A Lightweight Vehicle Detection Model Based on Improved YOLOv11 by Zhe Zhang, Zhongyang Zhang, Gang Li, Chenxi Xia

“…Aiming at the problems of insufficient vehicle detection accuracy, high misdetection and omission rate, and heavy model computational burden caused by complex lighting conditions, target occlusion, and other factors in urban traffic scenarios, this paper proposes an improved lightweight detection network, ZZ-YOLO. …”
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Anomaly-Based Intrusion Detection System in Wireless Sensor Networks Using Machine Learning Algorithms by Belal Al-Fuhaidi, Zainab Farae, Farouk Al-Fahaidy, Gawed Nagi, Abdullatif Ghallab, Abdu Alameri

“…This model applied mutual information (MI) for feature selection and the synthetic minority oversampling technique (SMOTE) for solving the imbalanced dataset problem. …”
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AS-Faster-RCNN: An Improved Object Detection Algorithm for Airport Scene Based on Faster R-CNN by Zhige He, Yuanqing He

“…However, the existing detection models have the problems of degradation, lacking of detection capability for deformed and small objects and single feature extraction, causing low detection accuracy. …”
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Curvature-Based Change Detection in Road Segmentation: Ascending Hierarchical Clustering vs. K-Means by David Jaurès Fotsa-Mbogne, Addie Bernice Nguensie-Wakponou, Jean Michel Nlong, Marcellin Atemkeng, Maurice Tchuente

“…This approach aligns with the broader problem of change detection in a finite sequence of data indexed by a totally ordered set, which could represent either a time series or a spatial trajectory. …”
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Distributed Denial of Services (DDoS) attack detection in SDN using Optimizer-equipped CNN-MLP. by Sajid Mehmood, Rashid Amin, Jamal Mustafa, Mudassar Hussain, Faisal S Alsubaei, Muhammad D Zakaria

“…The SDN has several security problems because of its intricate design, even with all its amazing features. …”
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TPDTNet: Two-Phase Distillation Training for Visible-to-Infrared Unsupervised Domain Adaptive Object Detection by Siyu Wang, Xiaogang Yang, Ruitao Lu, Shuang Su, Bin Tang, Tao Zhang, Zhengjie Zhu

“…Cross-domain migration suffers from problems such as a lack of data annotations in the infrared domain and interdomain feature differences. …”
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Roman urdu hate speech detection using hybrid machine learning models and hyperparameter optimization by Waqar Ashiq, Samra Kanwal, Adnan Rafique, Muhammad Waqas, Tahir Khurshaid, Elizabeth Caro Montero, Alicia Bustamante Alonso, Imran Ashraf

“…Abstract With the rapid increase of users over social media, cyberbullying, and hate speech problems have arisen over the past years. Automatic hate speech detection (HSD) from text is an emerging research problem in natural language processing (NLP). …”
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Small Target Detection Algorithm for UAV Aerial Images Based on Improved YOLOv7-tiny by ZHANG Guanghua, LI Congfa, LI Gangying, LU Weidang

“…Second, to strengthen the feature extraction capability for multi-scale targets and improve the detection of small targets, a small-target detection layer is designed, leading to a tiny-target detection head that increases the model receptive field and better addresses the scale variance problem caused by drastic target size changes. …”
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Snow Leopard Infrared Camera Image Detection Method Based on Improved EfficientDet Model by DAI Tianhong, LIU Chao

“…Secondly, the Generative Adversarial Networks is used to transfer the domain of night infrared gray image, and the image prediction results before and after migration are fused to solve the problem of weak target recognition ability in infrared image.Finally, the attention mechanism is added to the backbone feature extraction network to refine the feature map to improve the visual significance of snow leopard in RGB and infrared images, and the improved feature fusion network structure to integrate more effective information. …”
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An Effective Method for Detecting Cyber Attacks on Computer Networks from the NSL-KDD Data Set by Shaik Aseena Babu, Reddy Rajeswara, Vullam Nagagopi Raju, Reddy Gondi Konda, Shaik Subhani

“…Machine learning models are used to advance the techniques to detect and solve cybersecurity problems. Machine learning methods help detect more cyber attacks more efficiently than other software-oriented techniques, reducing the burden on security analysts. …”
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