Real time wire rope detection method based on Rockchip RK3588 by Mengpeng Qian, Yong Wang, Shaoqing Liu, Zhanghou Xu, Zhenshan Ji, Ming Chen, Hailong Wu, Zuchao Zhang

“…To enhance non-destructive wire rope inspection, a Mini-YOLO model was developed by integrating MobileNetV3, the Coordinate Attention (CA) mechanism, and a novel loss function, Inner-IoU, into the YOLOv8 framework. This paper’s innovation lies not in creating algorithmic components from scratch, but in their synergistic integration and targeted optimization to solve the specific challenges of real-time defect detection on resource-constrained edge devices. …”
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An improved lightweight tiny-person detection network based on YOLOv8: IYFVMNet by Fan Yang, Lihu Pan, Hongyan Cui, Linliang Zhang

“…IntroductionIn the aviation field, drone search and rescue is a highly urgent task involving small target detection. In such a resource-constrained scenario, there are challenges of low accuracy and high computational requirements.MethodsThis paper proposes IYFVMNet, an improved lightweight detection network based on YOLOv8. …”
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Object detection with afordable robustness for UAV aerial imagery: model and providing method by Viacheslav Moskalenko, Artem Korobov, Yuriy Moskalenko

“…The model and method for ensuring the robustness of resource-constrained neural network systems for object detection in aerial video surveillance. …”
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Review of Fault Detection and Diagnosis Methods in Power Plants: Algorithms, Architectures, and Trends by Camelia Adela Maican, Cristina Floriana Pană, Daniela Maria Pătrașcu-Pană, Virginia Maria Rădulescu

“…Key findings are summarized in a comparative matrix, highlighting trends, gaps, and inconsistencies across publication sources. This review identifies critical research gaps—including the underuse of hybrid models, lack of benchmark datasets, and limited integration between detection and control layers—and offers concrete recommendations for future research. …”
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SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

“…Furthermore, SGSNet has a computational cost of only 14.7 GFLOPs and a parameter count as low as 5.86 million, demonstrating an effective balance between high performance and resource efficiency.DiscussionLightweight deep learning model SGSNet not only exceeds the mainstream model in detection accuracy, but also greatly reduces the need for computing resources and is suitable for portable devices. …”
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Detection of Elementary White Mucosal Lesions by an AI System: A Pilot Study by Gaetano La Mantia, Federico Kiswarday, Giuseppe Pizzo, Giovanna Giuliana, Giacomo Oteri, Mario G. C. A. Cimino, Olga Di Fede, Giuseppina Campisi

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Gold nanobiosensors and Machine Learning: Pioneering breakthroughs in precision breast cancer detection by Soheil Sadr, Ashkan Hajjafari, Abbas Rahdar, Sadanand Pandey, Parian Poorjafari Jafroodi, Narges Lotfalizadeh, Mahdi Soroushianfar, Shahla Salimpour Kavasebi, Zelal Kharaba, Sonia Fathi-karkan, Hassan Borji

“…These sensors take advantage of the unique optical and electric properties that gold nanoparticles have, enabling them to achieve an accurate molecular level of detection. Gold nanobiosensors have been significantly developed through innovations like signal amplification and surface functionalization, integrated with the use of advanced imaging techniques. …”
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Securing Electric Vehicle Performance: Machine Learning-Driven Fault Detection and Classification by Mahbub Ul Islam Khan, Md. Ilius Hasan Pathan, Mohammad Mominur Rahman, Md. Maidul Islam, Mohammed Arfat Raihan Chowdhury, Md. Shamim Anower, Md. Masud Rana, Md. Shafiul Alam, Mahmudul Hasan, Md. Shohanur Islam Sobuj, Md. Babul Islam, Veerpratap Meena, Francesco Benedetto

“…In addition, the superiority of the proposed fault detection and classification approaches using ML tools was assessed by comparing the detection and classification efficiency through some statistical performance parameter comparisons among the classifiers.…”
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Effect of cochlear implant surgery on vestibular function: meta-analysis study by Iman Ibrahim, Sabrina Daniela da Silva, Bernard Segal, Anthony Zeitouni

“…No significant effect of CI surgery was detected in HIT, posturography, or DHI scores. Overall, the clinical effect of CI surgery on the vestibular function was found to be insignificant. …”
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Automated identification of soil functional components based on NanoSIMS data by Yahan Hu, Johann Maximilian Zollner, Carmen Höschen, Martin Werner, Steffen A. Schweizer

“…The tool is provided as an open-source software toolbox (NanoT). In addition, a two-step unsupervised segmentation method was developed to identify soil functional components based on NanoSIMS analyses. …”
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Failure Law of Sandstone and Identification of Premonitory Deterioration Information Based on Digital Image Correlation–Acoustic Emission Multi-Source Information Fusion by Zhaohui Chong, Guanzhong Qiu, Xuehua Li, Qiangling Yao

“…Additionally, by introducing the derivative functions of the multi-source information function for quantitative analysis, a comprehensive evaluation method was proposed based on the multi-source information fusion monitoring to forewarn red sandstone failure by levels during loading. …”
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A Hybrid and Modular Integration Concept for Anomaly Detection in Industrial Control Systems by Christian Goetz, Bernhard G. Humm

“…Therefore, in this paper, we present a modular and hybrid concept that enables the integration of efficient and effective anomaly detection while optimising the use of available resources under consideration of industrial requirements. …”
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Quantifying Truthfulness: A Probabilistic Framework for Atomic Claim-Based Misinformation Detection by Fahim Sufi, Musleh Alsulami

“…This paper addresses this gap by proposing a novel probabilistic framework that decomposes complex assertions into semantically atomic claims and computes their veracity through a structured evaluation of source credibility and evidence frequency. Each atomic unit is matched against a curated corpus of 11,928 cyber-related news entries using a binary alignment function, and its truthfulness is quantified via a composite score integrating both source reliability and support density. …”
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Optimizing Pre-Trained Code Embeddings With Triplet Loss for Code Smell Detection by Ali Nizam, Ertugrul Islamoglu, Omer Kerem Adali, Musa Aydin

“…Although code embedding-based systems have been successfully applied to various source code analysis tasks, further research is required to enhance code embedding for better code analysis capabilities, aiming to surpass the performance and functionality of static code analysis tools. …”
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Developing a Machine Vision System to Detect Weeds from Potato Plant by Yousef Abbaspour Gılandeh, Hossein Javadıkıa, Sajad Sabzı

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An Efficient Algorithm for Small Livestock Object Detection in Unmanned Aerial Vehicle Imagery by Wenbo Chen, Dongliang Wang, Xiaowei Xie

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Social Network Community Detection by Combining Self-Organizing Maps and Genetic Algorithms by Mehdi Ellouze

“…To this end, many research works in the literature offer users some tools that can help them take advantage of this mine of information. Community detection is one of these tools and aims to detect a set of entities that share some features within a social network. …”
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An enhanced lightweight model for apple leaf disease detection in complex orchard environments by Ge Wang, Wenjie Sang, Fangqian Xu, Yuteng Gao, Yue Han, Qiang Liu

“…However, in complex natural environments, factors such as light variations, shading from branches and leaves, and overlapping disease spots often result in reduced accuracy in detecting apple diseases. To address the challenges of detecting small-target diseases on apple leaves in complex backgrounds and difficulty in mobile deployment, we propose an enhanced lightweight model, ELM-YOLOv8n.To mitigate the high consumption of computational resources in real-time deployment of existing models, we integrate the Fasternet Block into the C2f of the backbone network and neck network, effectively reducing the parameter count and the computational load of the model. …”
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YOLOX-LS: Strong Gravitational Lenses Detection in the DECaLS with Deep Learning by Yangyang Liu, Liangping Tu, Jianxi Li, Jiawei Miao, Gengqi Lin, Chenying Zhao

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Application of VGG16 in Automated Detection of Bone Fractures in X-Ray Images by Resky Adhyaksa, Bedy Purnama

“…The training and testing phases utilized an 80:20 split of the data, employing binary cross-entropy as the loss function and the Adam optimizer for efficient weight updates. …”
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