A new approach for the detection of genetic alterations utilizing modified loop-mediated isothermal amplification reaction (LAMP) by Aneta Cierzniak, Małgorzata Małodobra-Mazur, Miron Tokarski

“…Current methods are hindered by complex workflows, requiring advanced equipment, skilled personnel, and invasive tissue sampling. …”
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Ultrasound-assisted DLLME with natural deep eutectic solvent and smartphone-based colorimetry for Pb(II) detection in water by Nayyer Azhdari, Biuck Habibi, Zahra Ayazi, Elaheh Rahimpour

“…This research presents a novel, cost-efficient and high-performance method for preconcentration and detection of lead ions [Pb(II)] using ultrasound-assisted dispersive liquid-liquid microextraction (USA-DLLME) combined with digital image colorimetry (DIC). …”
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Digitization of Architectural Heritage Objects Using Photogrammetry: Sumy Region Case Study by Ihor Tytarenko, José Machado, Ivan Pavlenko

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PIFR: A novel approach for analyzing pose angle-based human activity to automate fall detection in videos. by Vungsovanreach Kong, Saravit Soeng, Munirot Thon, Wan-Sup Cho, Anand Nayyar, Tae-Kyung Kim

“…The method outperforms existing approaches by effectively capturing complex geometric changes during fall events. The system is applicable to smart homes, wearable devices, and healthcare monitoring platforms, offering a scalable, reliable, and efficient solution to enhance safety and independence for elderly individuals, thereby contributing to advancements in health-monitoring technology.…”
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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

“…In this field, machine learning (ML) techniques are attracting growing attention due to their capability to recognize complex patterns, making them very suitable for the identification of damages in operating mechanical structures. …”
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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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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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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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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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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 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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Federated learning with LSTM for intrusion detection in IoT-based wireless sensor networks: a multi-dataset analysis by Raja Waseem Anwar, Mohammad Abrar, Abdu Salam, Faizan Ullah

“…Traditional centralized intrusion detection systems (IDS) face significant challenges in data privacy, computational efficiency, and scalability, particularly in resource-constrained IoT environments. …”
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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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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

“…Machine learning techniques are used to detect diseases based on the extracted features. In contrast, deep learning techniques learn complex patterns from large datasets without explicit feature extraction techniques and are well-suited for disease detection tasks. …”
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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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A Lightweight YOLOv8s Algorithm for Ceiling Fan Blade Defect Detection With Optimized Pruning and Knowledge Distillation by Qinyuan Huang, Chen Fan, Yuqi Sun, Jiaxiong Huang, Wengziyang Jiang

“…Detecting these surface defects is crucial; however, accurate and rapid detection typically involves complex machine vision algorithms, such as You Only Look Once (YOLO) networks, that require considerable computing resources, which contradicts the industry’s preference for simpler algorithms that can be deployed using low-cost computing power. …”
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Application of Improved YOLOv8 Image Model in Urban Manhole Cover Defect Management and Detection: Case Study by Yanqiong Ding, Baojiang Han, Hua Jiang, Hao Hu, Lei Xue, Jiasen Weng, Zhili Tang, Yuzhang Liu

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Dynamic Wireless Power Transfer System for Indoor AGV With a Distance-Measurement-Based Position Detection Technique by Deniss Stepins, Janis Zakis, Aleksandrs Sokolovs, Oleksandr Husev, Ryszard Strzelecki, Rik W. de Doncker

“…However, the cost and level of complexity of the position detection system are moderately lower and the proposed position detection system is immune to optical radiation and magnetic fields. …”
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