Mixed image detection method of belt coal blockage and leakage based on improved RetinaNet mode by Qingjun Fu, Xiang Liu, Yinqiang Yan, Zhibin Guo

“…The test results show that this method can comprehensively collect the images of coal conveying by belt, and accurately identify the detection of coal blockage and coal leakage. This method is applied to the actual production environment, which can monitor the situation of belt coal transportation in real time and accurately detect coal blockage and leakage, which is of great significance to improve the production efficiency of coal transportation, reduce economic losses and ensure production safety.…”
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Detection Model for 5G Core PFCP DDoS Attacks Based on Sin-Cos-bIAVOA by Zheng Ma, Rui Zhang, Lang Gao

“…The development of 5G environments has several advantages, including accelerated data transfer speeds, reduced latency, and improved energy efficiency. Nevertheless, it also increases the risk of severe cybersecurity issues, including a complex and enlarged attack surface, privacy concerns, and security threats to 5G core network functions. …”
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gamUnet: designing global attention-based CNN architectures for enhanced oral cancer detection and segmentation by Jinyang Zhang, Hongxin Ding, Hongxin Ding, Runchuan Zhu, Weibin Liao, Weibin Liao, Junfeng Zhao, Junfeng Zhao, Min Gao, Xiaoyun Zhang

“…Additionally, we introduce an extended model, gamResNet, to further improve OSCC detection performance. Both architectures show significant improvements in handling the unique challenges of oral cancer images.ResultsExtensive experiments on public datasets show that our GAM-enhanced architecture significantly outperforms conventional models, achieving superior accuracy, robustness, and efficiency in OSCC diagnosis.DiscussionOur approach provides an effective tool for clinicians in diagnosing OSCC, reducing diagnostic variability, and ultimately contributing to improved patient care and treatment planning.…”
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LGR-Net: A Lightweight Defect Detection Network Aimed at Elevator Guide Rail Pressure Plates by Ruizhen Gao, Meng Chen, Yue Pan, Jiaxin Zhang, Haipeng Zhang, Ziyue Zhao

“…LGR-Net achieves low computational complexity and high detection accuracy, providing an efficient and effective solution for defect detection in elevator guide rail pressure plates.…”
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Multi-Domain Controversial Text Detection Based on a Machine Learning and Deep Learning Stacked Ensemble by Jiadi Liu, Zhuodong Liu, Qiaoqi Li, Weihao Kong, Xiangyu Li

“…Firstly, considering the multidimensional complexity of textual features, we integrate comprehensive feature engineering, i.e., encompassing word frequency, statistical metrics, sentiment analysis, and comment tree structure features, as well as advanced feature selection methodologies, particularly lassonet, i.e., a neural network with feature sparsity, to effectively address dimensionality challenges while enhancing model interpretability and computational efficiency. …”
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Forced Oscillation Detection via a Hybrid Network of a Spiking Recurrent Neural Network and LSTM by Xiaomei Yang, Jinfei Wang, Xingrui Huang, Yang Wang, Xianyong Xiao

“…Deep learning (DL) holds significant potential for detecting forced oscillations correctly. However, existing artificial neural networks (ANNs) face challenges when employed in edge devices for timely detection due to their inherent complex computations and high power consumption. …”
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Optimized Ensemble Deep Learning for Real-Time Intrusion Detection on Resource-Constrained Raspberry Pi Devices by Muhammad Bisri Musthafa, Samsul Huda, Tuy Tan Nguyen, Yuta Kodera, Yasuyuki Nogami

“…Deep learning techniques offer promising solutions for such detection due to their superior complex pattern recognition and anomaly detection capabilities in large datasets. …”
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MonoDFM: Density Field Modeling-Based End-to-End Monocular 3D Object Detection by Gang Liu, Xinrui Huang, Xiaoxiao Xie

“…Moreover, compared with more complex approaches like Neural Radiance Fields (NeRF), MonoDFM provides a streamlined and efficient prediction process. …”
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YS3AM: Adaptive 3D Reconstruction and Harvesting Target Detection for Clustered Green Asparagus by Si Mu, Jian Liu, Ping Zhang, Jin Yuan, Xuemei Liu

“…Extracting precise stem details in complex spatial arrangements is a challenge. This paper explored the YS3AM (Yolo-SAM-3D-Adaptive-Modeling) method for detecting green asparagus and performing 3D adaptive-section modeling using a depth camera, which could benefit harvesting path planning for selective harvesting robots. …”
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DSAT: a dynamic sparse attention transformer for steel surface defect detection with hierarchical feature fusion by Shouluan Wu, Hui Yang, Liefa Liao, Chao Song, Yating Fang, Jianglong Fu, Tan Li

“…These defects exhibit diverse morphological characteristics and complex patterns, which pose substantial challenges to traditional detection models, particularly regarding multi-scale feature extraction and information retention across network depths. …”
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FDIA Attack Detection Technique for Smart Grids Based on Graph Reconstruction and Spatio-Temporal Joint Modeling by Gao Yuzhang, Xia Jing

“…With the widespread application of smart grids, the false data injection attack (FDIA) has become a major threat to power grid security. Traditional detection methods often have difficulty in effectively identifying such attacks, especially in complex environments. …”
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Hierarchical Attention Module-Based Hotspot Detection in Wafer Fabrication Using Convolutional Neural Network Model by Mobeen Shahroz, Mudasir Ali, Alishba Tahir, Henry Fabian Gongora, Carlos Uc Rios, Md Abdus Samad, Imran Ashraf

“…As integrated circuits continue to grow in complexity, doing efficient yield analyses is becoming more essential but also more difficult. …”
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Enhanced YOLOv8-based method for space debris detection using cross-scale feature fusion by Yang Guo, Xianlong Yin, Yao Xiao, Zhengxu Zhao, Xu Yang, Chenggang Dai

“…The experimental results show that the detection accuracy and speed of the method are improved, and that they can meet the requirements of space debris detection in complex backgrounds.…”
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A comprehensive systematic review of intrusion detection systems: emerging techniques, challenges, and future research directions by Arjun Kumar Bose Arnob, Rajarshi Roy Chowdhury, Nusrat Alam Chaiti, Sudipta Saha, Ajoy Roy

“… The role of Intrusion Detection Systems (IDS) in the protection against the increasing variety of cybersecurity threats in complex environments, including the Internet of Things (IoT), cloud computing, and industrial networks. …”
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SDFSD-v1.0: A Sub-Meter SAR Dataset for Fine-Grained Ship Detection by Peixin Cai, Bingxin Liu, Peilin Wang, Peng Liu, Yu Yuan, Xinhao Li, Peng Chen, Ying Li

“…In the field of target detection, a prominent area is represented by ship detection in SAR imagery based on deep learning, particularly for fine-grained ship detection, with dataset quality as a crucial factor influencing detection accuracy. …”
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Rotation-Invariant Feature Enhancement with Dual-Aspect Loss for Arbitrary-Oriented Object Detection in Remote Sensing by Zhao Hu, Xiangfu Meng, Xinsong Liu, Zhuxiang Sun

“…Evaluated on the DIOR-R and HRSC2016 benchmarks, our method demonstrates robust detection capabilities for arbitrarily oriented objects, achieving competitive performance in both accuracy and efficiency. …”
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R-Sparse R-CNN: SAR Ship Detection Based on Background-Aware Sparse Learnable Proposals by Kamirul Kamirul, Odysseas A. Pappas, Alin M. Achim

“…This unified design improves efficiency by eliminating redundant computation inherent in separate pooling. …”
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GCS-YOLO: A Lightweight Detection Algorithm for Grape Leaf Diseases Based on Improved YOLOv8 by Qiang Hu, Yunhua Zhang

“…The CBAM attention mechanism is added to the model to improve the extraction of subtle features of lesions in complex environments. Cross-scale shared convolution parameters and separated batch normalization techniques are used to optimize the detection head, achieving a lightweight design and improving the detection efficiency of the algorithm. …”
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Development of eco-friendly and cost-effective electrochemical sensor for the simultaneous detection of 4-aminophenol and paracetamol in water by Antía Fdez-Sanromán, Najib Ben Messaoud, Marta Pazos, Emilio Rosales, Raquel Barbosa Queirós

“…It was successfully tested in real freshwater samples, demonstrating high accuracy even in complex matrices. This innovative methodology provides a rapid, cost-effective, and portable analytical tool for routine monitoring of pharmaceutical contaminants, enabling more accurate environmental risk assessments and supporting the implementation of more efficient management strategies.…”
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ASIC Design for Real-Time CAN-Bus Intrusion Detection and Prevention System Using Random Forest by Junseok Lee, Sangmin Park, Sua Shin, Hyungchul Im, Joosock Lee, Seongsoo Lee

“…To address this issue, we designed an IDS that can immediately determine if an attack is present when receiving a CAN frame and blocking the attack node. Fast and efficient detection is possible complex matrix operations because the random forest model performs detection based on comparison operations. …”
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