Evaluation of Smartphones Equipped with Light Detection and Ranging Technology for Circumferential and Volumetric Measurements in Lower Extremity Lymphedema by Masato Tsuchiya, Kanako Abe, Satoshi Kubo, Ryuichi Azuma

“…Smartphones with light detection and ranging (LiDAR) technology may offer fast and efficient alternatives for three-dimensional imaging and measurement. …”
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Multi-Signal Induction Motor Broken Rotor Bar Detection Based on Merged Convolutional Neural Network by Tianyi Wang, Shiguang Wen, Shaotong Sheng, Huimin Ma

“…Traditional methods face challenges in motor broken rotor bar (BRB) detection: model-driven methods are difficult to apply accurately in complex and changing environments, while data-driven methods usually require sophisticated feature extraction and classification processes. …”
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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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Intelligent Stress Detection Using ECG Signals: Power Spectrum Imaging with Continuous Wavelet Transform and CNN by Rodrigo Mateo-Reyes, Irving A. Cruz-Albarran, Luis A. Morales-Hernandez

“…The proposed approach is characterized by its ability to transform ECG signals into time–frequency representations by means of short duration sampling, achieving an accurate classification of stress states without the need for complex feature extraction processes. This model is an efficient and accurate tool for stress analysis from biomedical signals.…”
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A Dual-Task Approach for Onset Time Picking and the Detection of Microseismic Waveforms Based on Deep Learning by Hang Zhang, Ruoyu Li, Chunchi Ma, Xiaobing Cheng, Simeng Meng, Zhenxing Huang, Di Li

“…Before the analysis of source information and further prediction of possible disasters, it is generally necessary to perform onset time picking and detection of microseismic signals. To improve the accuracy and efficiency of these tasks, this paper proposes an advanced deep dual-task neural network, which sequentially integrates the two processes. …”
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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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Research on detection and location method of safflower filament picking points during the blooming period in unstructured environments by Bangbang Chen, Feng Ding, Baojian Ma, Qijun Yao, Shanping Ning

“…Secondly, a novel lightweight segmentation detection head (LSDH) was introduced, based on the YOLO-SaFi model, to efficiently segment safflower filaments and fruit balls. …”
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Data leakage detection in machine learning code: transfer learning, active learning, or low-shot prompting? by Nouf Alturayeif, Jameleddine Hassine

“…However, automated tools with advanced ML techniques are increasingly recognized as essential for efficiently identifying quality issues in large and complex codebases, enhancing the overall effectiveness of code review processes. …”
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LS-MambaNet: Integrating Large Strip Convolution and Mamba Network for Remote Sensing Object Detection by Lingyu Yan, Zijian He, Zhiqi Zhang, Guangqi Xie

“…To address the above challenges, we propose a new target detection framework for complex remote sensing images, LS-MambaNet. …”
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An Optimally Oriented Coherence Attribute Method and Its Application to Faults and Fracture Sets Detection in Carbonate Reservoirs by Shuai Chen, Shengjun Li, Qi Ma, Lu Qin, Sanyi Yuan

“…Overall, the OOCA method offers a geologically consistent and computationally efficient solution for high-resolution fault interpretation and drilling risk prediction in structurally complex carbonate reservoirs.…”
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A robust and efficient approach to estimating the age of secondary mangrove forests employing time-series Landsat images and the CCDC model by Yue Zhang, Xiaoyan Li, Rong Zhang, Lina Cheng, Mingming Jia, Chuanpeng Zhao, Xianxian Guo, Haihang Zeng, Wensen Yu, Qian Shi, Zongming Wang

“…However, reliably determining mangrove forest age using remote sensing has been hindered by the complex dynamics of intertidal environments. To overcome these challenges, we developed a robust and efficient approach for estimating the age of secondary mangrove forests (ASMF) by integrating Landsat time-series data and the Continuous Change Detection and Classification (CCDC) algorithm. …”
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SOFTWARE COMPONENT DEVELOPMENT FOR PARALLEL GATEWAYS DETECTION AND QUALITY ASSESSMENT IN BPMN MODELS USING FUZZY LOGIC by Andrii Kopp, Ľuboš Cibák, Dmytro Orlovskyi, Dmytro Kudii

“…Errors in their implementation, such as incorrect synchronization or termination of parallel branches, are common and difficult to detect by traditional metrics such as the Number of Activities (NOA) or Control-Flow Complexity (CFC). …”
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Improving Fire and Smoke Detection with You Only Look Once 11 and Multi-Scale Convolutional Attention by Yuxuan Li, Lisha Nie, Fangrong Zhou, Yun Liu, Haoyu Fu, Nan Chen, Qinling Dai, Leiguang Wang

“…Although challenges remain in handling occluded targets and complex backgrounds, the model exhibits strong robustness and generalization capabilities, maintaining efficient detection performance in complicated environments.…”
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TCCDNet: A Multimodal Pedestrian Detection Network Integrating Cross-Modal Complementarity with Deep Feature Fusion by Shipeng Han, Chaowen Chai, Min Hu, Yanni Wang, Teng Jiao, Jianqi Wang, Hao Lv

“…Multimodal pedestrian detection has garnered significant attention due to its potential applications in complex scenarios. …”
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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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HPRT-DETR: A High-Precision Real-Time Object Detection Algorithm for Intelligent Driving Vehicles by Xiaona Song, Bin Fan, Haichao Liu, Lijun Wang, Jinxing Niu

“…This integration expands the model’s receptive field and enhances feature extraction without adding learnable parameters or complex computations, effectively minimizing missed detections of small targets. …”
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Fast Anomaly Detection for Vision-Based Industrial Inspection Using Cascades of Null Subspace PCA Detectors by Muhammad Bilal, Muhammad Shehzad Hanif

“…In this study, we introduce a novel anomaly detection framework that leverages feature maps from a lightweight convolutional neural network (CNN) backbone, MobileNetV2, and cascaded detection to achieve notable accuracy as well as computational efficiency. …”
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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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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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Enhanced diabetic retinopathy detection using U-shaped network and capsule network-driven deep learning by Govindharaj I, Poongodai A, Gnanajeyaraman Rajaram, Santhakumar D, Ravichandran S, Vijaya Prabhu R, Udayakumar K, Yazhinian S

“…Glaucoma, a severe eye disease leading to irreversible vision loss if untreated, remains a significant challenge in healthcare due to the complexity of its detection. Traditional methods rely on clinical examinations of fundus images, assessing features like optic cup and disc sizes, rim thickness, and other ocular deformities. …”
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