A new statistical metric for robust target detection in cryo-EM using 2D template matching by Kexin Zhang, Pilar Cossio, Aaditya V. Rangan, Bronwyn A. Lucas, Nikolaus Grigorieff

“…In this work, a novel 2DTM metric, referred to as the 2DTM p-value, is developed to extend the 2DTM framework to more complex applications. The 2DTM p-value combines information from two previously used 2DTM metrics, namely the 2DTM signal-to-noise ratio (SNR) and z-score, which are derived from the cross-correlation coefficient between the target and the template. …”
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Semi-Supervised Anomaly Detection for the Identification of Damages in an Aerospace Sandwich Structure Based on Synthetically Generated Strain Data by Florian Forsthuber, Christoph Kralovec, Martin Schagerl

“…The structural health monitoring (SHM) of safety relevant composite components is becoming increasingly relevant as it enables in-service diagnosis and data acquisition capabilities, contributing to the optimization and efficient operation of the overall system and ultimately saving costs and resources. …”
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A High Accuracy and Large-Scale Detection for Fixed-Wing UAV Autonomous Ground Landing With GNSS-Denied by Bin Fang, Zhiwei Zhong, Xiangjun Jiang

“…To further facilitate large-scale range detection in GNSS-denied conditions, a landing guidance window is developed, enabling the efficient search for and tracking of UAVs. …”
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SDKU-Net: A Novel Architecture with Dynamic Kernels and Optimizer Switching for Enhanced Shadow Detection in Remote Sensing by Gilberto Alvarado-Robles, Isac Andres Espinosa-Vizcaino, Carlos Gustavo Manriquez-Padilla, Juan Jose Saucedo-Dorantes

“…To address these issues, this study proposes the Supervised Dynamic Kernel U-Net (SDKU-Net), a novel architecture designed to enhance shadow detection in complex remote sensing scenarios. SDKU-Net integrates dynamic kernel adjustment, a combined loss function incorporating Focal and Tversky Loss, and optimizer switching to effectively tackle class imbalance and improve segmentation quality. …”
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Electrochemical Immunosensor Using COOH-Functionalized 3D Graphene Electrodes for Sensitive Detection of Tau-441 Protein by Sophia Nazir, Muhsin Dogan, Yinghui Wei, Genhua Pan

“…Early diagnosis of Alzheimer’s disease (AD) is essential for effective treatment; however current diagnostic methods are often complex, costly, and unsuitable for point-of-care testing. …”
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Development of a Fully Automated Microfluidic Electrochemical Sensor on the ESSENCE Platform for Rapid Detection of Single-Stranded DNA by Niranjan Haridas Menon, Maryom Rahman, Sagnik Basuray

“…This study presents a fully automated microfluidic electrochemical sensor for the detection of single-stranded DNA (ssDNA) on the ESSENCE platform. …”
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YOLO-AMM: A Real-Time Classroom Behavior Detection Algorithm Based on Multi-Dimensional Feature Optimization by Yi Cao, Qian Cao, Chengshan Qian, Deji Chen

“…However, the existing models are still deficient in detail feature capture capability, multi-layer feature correlation, and multi-scale target adaptability, making it challenging to realize high-precision real-time detection in complex scenes. This paper proposes an improved classroom behavior detection algorithm, YOLO-AMM, to solve these problems. …”
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Effective DDoS attack detection in software-defined vehicular networks using statistical flow analysis and machine learning. by Himanshi Babbar, Shalli Rani, Maha Driss

“…The ML models, especially complex ones like Random Forest, require substantial processing power, which necessitates efficient data handling and possibly leveraging edge computing resources to reduce latency. …”
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A Chelating Resin of EDTA-Type Modified Cross-Linking Polystyrene to Preconcentrate Trace Metals for Seawater Detection by Chao Li, Linna Duan, Mingchao Han, Hongwei He, Mengxiang Yuan, Hairong Wang

“…Compared with the conventional solvent method, the novel material and enrichment device have high preconcentration efficiency, strong anti-interference ability, and low cost and could be directly applied for routine seawater detection.…”
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Exploring the Application of Large Language Models Based AI Agents in Leakage Detection of Natural Gas Valve Chambers by Qian Wei, Hongjun Sun, Yin Xu, Zisheng Pang, Feixiang Gao

“…The traditional detection methods highly depend on manpower with large workload and are prone to missed and false alarms, which seriously affects the efficiency and safety of oil and gas production and transportation. …”
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An Improved YOLOv8-Based Dense Pedestrian Detection Method with Multi-Scale Fusion and Linear Spatial Attention by Han Gong, Tian Li, Lijuan Wang, Shucheng Huang, Mingxing Li

“…Simultaneously, a multi-scale linear spatial attention module is designed to amplify features of visible parts of occluded pedestrians while suppressing interference from complex backgrounds. Secondly, a small-scale pedestrian detection head is introduced in the neck of the YOLOv8 network to enhance detection performance for diminutive pedestrians. …”
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Discussion on Matrix Interference in Trace-Level Bromate Detection of Natural Mineral Water in Southwest China Karst Area by Xi YANG, Xiaolin ZHOU, Song ZHENG

“…The bromate in natural mineral water in the Guizhou karst area of southwest China is usually at trace levels while the chemical background of water is complex, which causes great difficulties using ion chromatography to detect the bromate due to matrix interference. …”
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Deep learning for rice leaf disease detection: A systematic literature review on emerging trends, methodologies and techniques by Chinna Gopi Simhadri, Hari Kishan Kondaveeti, Valli Kumari Vatsavayi, Alakananda Mitra, Preethi Ananthachari

“…This review also discusses the limitations of existing studies and presents future directions for further developing more robust and efficient rice leaf disease detection techniques.…”
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A deep learning approach to detect diseases in pomegranate fruits via hybrid optimal attention capsule network by P. Sajitha, A. Diana Andrushia, N. Anand, M.Z. Naser, Eva Lubloy

“…In post-harvest pomegranate fruit disease detection, deep learning has great potential to extract complex patterns and features from large datasets. …”
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LI-YOLOv8: Lightweight small target detection algorithm for remote sensing images that combines GSConv and PConv. by Pingping Yan, Xiangming Qi, Liang Jiang

“…In the domain of remote sensing image small target detection, challenges such as difficulties in extracting features of small targets, complex backgrounds that easily lead to confusion with targets, and high computational complexity with significant resource consumption are prevalent. …”
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Multi-stream feature fusion of vision transformer and CNN for precise epileptic seizure detection from EEG signals by Qi Li, Wei Cao, Anyuan Zhang

“…Conclusions The CMFViT model provides an efficient, accurate, and innovative solution for complex EEG signal analysis and seizure detection tasks for single and cross-subjects while laying the foundation for developing real-time, accurate seizure detection systems.…”
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DCA-YOLOv8: A Novel Framework Combined with AICI Loss Function for Coronary Artery Stenosis Detection by Hualin Duan, Sanli Yi, Yanyou Ren

“…In order to improve the accuracy and efficiency of detection, a new deep-learning technique based on a coronary artery stenosis detection framework (DCA-YOLOv8) is proposed in this paper. …”
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Self-DSNet: A Novel Self-ONNs Based Deep Learning Framework for Multimodal Driving Distraction Detection by Mamun Or Rashid, Md. Mosarrof Hossen, Mohammad Nashbat, Mazhar Hasan-Zia, Ali K. Ansaruddin Kunju, Amith Khandakar, Azad Ashraf, Molla Ehsanul Majid, Saad Bin Abul Kashem, Muhammad E. H. Chowdhury

“…To address these challenges, we propose a novel model, Self-DSNet, for efficient driving distraction detection. The proposed Self-DSNet model utilizes Self-Organizing Neural Network (Self-ONN) layers to enhance complex pattern learning within the data. …”
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EMHANet: Lightweight Salient Object Detection for Remote Sensing Images via Edge-Aware Multiscale Feature Fusion by Qian Tang, Zhen Wang, Xuqi Wang, Shan-Wen Zhang

“…The network employs a coarse-to-fine strategy to accurately detect salient objects while maintaining efficiency. …”
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Acoustic Signal-Based Deep Learning Approach and Device for Detecting Interfacial Voids in Steel–Concrete Composite Structures by Wei Tian, Hang Yuan, Xinpeng You, Hehui Zheng, Bazhou Li, Chengming Peng

“…Developed tracked magnetic inspection robots can be applied to a variety of towering and complex confined areas, with real-time inspection efficiency as high as 0.1 m2/s. …”
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