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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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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Optimization and Validation of Universal Real-Time RT-PCR Assay to Detect Virulent Newcastle Disease Viruses by Ellen Ruth Alexander Morris, Megan E. Schroeder, Phelue N. Anderson, Lisa J. Schroeder, Nicholas Monday, Gabriel Senties-Cue, Martin Ficken, Pamela J. Ferro, David L. Suarez, Kiril M. Dimitrov

“…The considerable genetic diversity of the virus adds complexity to maintaining the high sensitivity and specificity of molecular detection assays. …”
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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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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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Anomaly Detection in Industrial Machine Sounds Using High-Frequency Features and Gate Recurrent Unit Networks by Thi-Thu-Huong Le, Andro Aprila Adiputra, Jiwon Yun, Howon Kim

“…Detecting anomalies in industrial sound is critical for maintaining operational efficiency, preventing costly equipment failures, and ensuring workplace safety. …”
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A multiple biomolecules-based rapid life detection protocol embedded in a rover scientific subsystem for soil sample analysis by Akib Zaman, Fardeen Ashraf, Haseena Khan, Faria Noshin Ahona, Oliullah Samir, Asif Mahmud Rayhan, Sadia Nur Nazifa, Hafsah Mahzabin Chowdhury, Md. Mahbubur Rahman

“…This research focuses on the objective of the extraterrestrial life detection domain and seeks to provide an efficient protocol that can produce life detection decisions based on empirical data obtained through chemical analysis under time and resource-constrained conditions. …”
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Research on UAV aerial imagery detection algorithm for Mining-Induced surface cracks based on improved YOLOv10 by Jiayong An, Siyuan Dong, Xuanli Wang, Chenlei Li, Wenpei Zhao

“…However, detection is challenged by small crack size, complex morphology, large scale variation, and uneven spatial distribution, further exacerbated by UAVs’ limited onboard computational capacity. …”
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Tomato yellow leaf curl virus detection based on cross-domain shared attention and enhanced BiFPN by Henghui Mo, Linjing Wei

“…This model exhibits exceptional performance in detecting TYLCV in complex environments, providing robust technical support for tomato growth monitoring and offering insights for the detection of other crop diseases. …”
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CSEANet: Cross-Stage Enhanced Aggregation Network for Detecting Surface Bolt Defects in Railway Steel Truss Bridges by Yichao Chen, Yifan Sun, Ziheng Qin, Zhipeng Wang, Yixuan Geng

“…While UAV-based approaches have recently been developed, they still encounter significant technical obstacles, including small target recognition, background complexity, and computational limitations. To overcome these challenges, CSEANet is introduced—an improved YOLOv8-based framework tailored for bolt defect detection. …”
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Integrating Stride Attention and Cross-Modality Fusion for UAV-Based Detection of Drought, Pest, and Disease Stress in Croplands by Yan Li, Yaze Wu, Wuxiong Wang, Huiyu Jin, Xiaohan Wu, Jinyuan Liu, Chen Hu, Chunli Lv

“…This study demonstrates that the integration of lightweight attention mechanisms with multimodal UAV remote sensing imagery enables efficient, accurate, and scalable agricultural disaster detection under complex field conditions.…”
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Employing CNN mobileNetV2 and ensemble models in classifying drones forest fire detection images by Dima Suleiman, Ruba Obiedat, Rizik Al-Sayyed, Shadi Saleh, Wolfram Hardt, Yazan Al-Zain

“… In recent years, the adoption of advanced machine learning techniques has revolutionized approaches to solving complex problems, such as identifying occurrences of forest fires. …”
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Intelligent GPR Detection of Backfill Grouting Quality and Adjacent Soil Cavities in Shield Tunnels: A Case Study by Guangyuan Cai, Xiongyao Xie, Kang Li

“…This research advances the automation and intelligence of backfill grouting and cavity detection, supporting the safe and efficient progress of shield tunnel construction.…”
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Detection of Crack Sealant in the Pretreatment Process of Hot In-Place Recycling of Asphalt Pavement via Deep Learning Method by Kai Zhao, Tianzhen Liu, Xu Xia, Yongli Zhao

“…They often appear as wide black patches that overlap with cracks and potholes, and complex background noise further complicates detection. …”
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Lightweight YOLOv8 for tongue teeth marks and fissures detection based on C2f_DCNv3 by Chunyang Jin, Delong Zhang, Xiyuan Cao, Zhidong Zhang, Chenyang Xue, Yanjun Zhang

“…Additionally, the model reduces computational cost by approximately one-third in terms of FLOPS, maintaining high accuracy while greatly decreasing the number of parameters, thus offering a more robust and resource-efficient solution. For tongue crack detection, the mAP increases to 91.34%, with notable improvements in F1 score, precision, and recall. …”
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Analyzing Taiwanese Traffic Patterns on Consecutive Holidays Through Forecast Reconciliation and Prediction-Based Anomaly Detection Techniques by Mahsa Ashouri, Frederick Kin Hing Phoa, Marzia Angela Cremona

“…Being based on OLS, it is efficient and permits avoiding the computational burden of more complex methods. …”
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MDFusion: Multi-Dimension Semantic–Spatial Feature Fusion for LiDAR–Camera 3D Object Detection by Renzhong Qiao, Hao Yuan, Zhenbo Guan, Wenbo Zhang

“…Extensive experiments on the KITTI and ONCE datasets demonstrate that our method achieves competitive performance in complex scenes, significantly improving the multi-modal fusion quality and detection accuracy while maintaining computational efficiency.…”
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Novel Europium-Grafted 3D Covalent Organic Framework for Selective and Sensitive Fluorescence-Enhanced Detection of Levofloxacin by Junyi Zhao, Chao Zhang, Zhijie Qiu, Zerong Zhang, Xiaorou Lin, Shibin Huang, Jianfeng Zhang, Jingpeng Wu, Li Liao, Rui Wang

“…Levofloxacin (LVFX), a fluoroquinolone antibacterial agent widely used in treating bacterial infections, poses significant risks when overused, necessitating the development of reliable and efficient detection methods. Herein, we introduce Eu@SUZ−103, a novel europium-grafted three-dimensional covalent organic framework (COF) featuring an eight-connected <b><i>bcu</i></b> net, for the selective detection of LVFX in serum and urine. …”
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Comparative evaluation of voltage conversion and encoder pulse detection methods for controlling a model high-bay warehouse by Anas Abu Al-Hija’a, B. J. Szekeres, M. Andó

“…The presented evaluation enhances control strategies for industrial automation, emphasizing efficient voltage conversion and precise encoder pulse detection to enhance system performance and reliability, laying the groundwork for future advancements in remote control capabilities and complex manufacturing systems.…”
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A Comparative Analysis of Support Vector Machine and K-Nearest Neighbors Models for Network Attack Traffic Detection by Han Zhuoxi

“…The results indicate that the SVM model excels in handling high-dimensional and intricate data, demonstrating its capability to tackle the complexity of modern cyber threats. On the other hand, KNN proves to be more efficient and straightforward when applied to less complex data structures. …”
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