Forecast of the morphology and occurrence conditions of complex chromite ore bodies (on example of Labogeyskoe-2 site, Polar Urals) by T. P. Morozova, E. V. Karelina, V. E. Markov

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Indocyanine Green and Arginine-Glycine-Aspartic Acid Complex Used in Intraoperative Visualization during Resection of Bladder Tumour by Li Peng, I. R. Kabirov, A. R. Kasinskaya, Jiaqi Wang, Wanhai Xu, E. K. Zhuk, R. A. Nuralieva

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Dynamic Aerial Small Target Detection Algorithm Based on Compound Zoom Scaling by Jiang Yuan, Zhu Gaofeng, Zhu Fenghua, Xiong Gang

“…Experiments conducted on the VisDrone2019 UAV aerial ima-gery dataset demonstrate that the proposed algorithm improves mAP by 2.1%, reduces FLOPs by 32.5%, and decreases computational complexity, resulting in superior detection performance.…”
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Anomaly detection and removal strategies for in-line permittivity sensor signal used in bioprocesses by Emils Bolmanis, Emils Bolmanis, Emils Bolmanis, Selina Uhlendorff, Miriam Pein-Hackelbusch, Vytautas Galvanauskas, Oskars Grigs

“…Trivial approaches, such as moving average filtering, do not adequately capture the complexity of the problem. However, our method provides a structured solution through three consecutive steps: 1) Signal preprocessing to reduce noise and eliminate context dependency; 2) Anomaly detection using threshold-based identification; 3) Validation and removal of identified anomalies.Results and discussionWe demonstrate that our approach effectively detects and removes anomalies by compensating signal shift value, while remaining computationally efficient and practical for real-time use. …”
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Vehicle detection in drone aerial views based on lightweight OSD-YOLOv10 by Yang Zhang, Xiaobing Chen, Su Sun, Hongfeng You, Yuanyuan Wang, Jianchu Lin, Jiacheng Wang

“…Compared to other YOLO series and lightweight models, OSD-YOLOv10 exhibits superior detection accuracy and lower computational complexity, achieving an optimal balance between high accuracy and low resource consumption. …”
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Hierarchical Mixed-Precision Post-Training Quantization for SAR Ship Detection Networks by Hang Wei, Zulin Wang, Yuanhan Ni

“…Convolutional neural network (CNN)-based synthetic aperture radar (SAR) ship detection models operating directly on satellites can reduce transmission latency and improve real-time surveillance capabilities. …”
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Lightweight Small Target Detection Algorithm Based on YOLOv8 Network Improvement by Xiaoyi Hao, Ting Li

“…The modules have been designed to optimise feature extraction and improve model efficiency. The paper also discusses the challenges associated with low accuracy in small target detection and high model complexity in UAV applications. …”
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Asynchronous Real-Time Federated Learning for Anomaly Detection in Microservice Cloud Applications by Mahsa Raeiszadeh, Amin Ebrahimzadeh, Roch H. Glitho, Johan Eker, Raquel A. F. Mini

“…Our FL approach updates the global model in an asynchronous manner to achieve accurate and efficient anomaly detection, addressing computational overhead across diverse edge clients, including those that experience delays. …”
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OW-YOLO: An Improved YOLOv8s Lightweight Detection Method for Obstructed Walnuts by Haoyu Wang, Lijun Yun, Chenggui Yang, Mingjie Wu, Yansong Wang, Zaiqing Chen

“…These improvements effectively reduced model complexity and significantly enhanced detection accuracy for obstructed walnuts. …”
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An optimized stacking-based TinyML model for attack detection in IoT networks. by Anshika Sharma, Shalli Rani, Mohammad Shabaz

“…With the expansion of Internet of Things (IoT) devices, security is an important issue as attacks are constantly gaining more complex. Traditional attack detection methods in IoT systems have difficulty being able to process real-time and access limitations. …”
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Target Detection and Image Enhancement for Underwater Environment: Research on Improving YOLOv7 by Yang Luo, Wen Feng

“…Aiming at the common low accuracy and efficiency problems in underwater target detection, this paper designs an innovative algorithm based on the YOLOv7 framework. …”
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A policy conflict detection mechanism for multi-controller software-defined networks by You Lu, Qiming Fu, Xuefeng Xi, Zhenping Chen, Encen Zou, Baochuan Fu

“…The experimental results under the campus network environment prove that our method can effectively detect the conflict of flow policies existing in the multi-controller software-defined network and has advantages over the existing methods in the integrity, accuracy, and efficiency of the detection.…”
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Advances in research on novel technologies for the detection of exogenous contaminants in traditional Chinese medicine by Ziyu Guo, Junyao Li, Lina Zeng, Ping Wang, Meifang Li, Chang Su, Shuhong Wang

“…Exogenous contaminants in traditional Chinese medicine (TCM), including pesticide residues, heavy metals, mycotoxins, and sulfur dioxide residues, pose significant risks to human health and environmental safety. Conventional detection methods are limited by insufficient sensitivity, complex sample preparation, and challenges in multi-residue analysis, compromising accuracy and efficiency. …”
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IMPLEMENTATION OF K-MEDOIDS AND K-PROTOTYPES CLUSTERING FOR EARLY DETECTION OF HYPERTENSION DISEASE by Hardianti Hafid, Selvi Annisa

“…The clustering results show K-Medoids' superiority in grouping data with higher Silhouette Coefficient values ​​compared to K-Prototypes. Overall, the K-Medoids and K-Prototypes algorithms can detect early hypertension risk by dividing patients into different risk groups. …”
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Mode Selection Model for Rail Crack Detection Based on Ultrasonic Guided Waves by Bo Xing, Zujun Yu, Xining Xu, Liqiang Zhu, Hongmei Shi

“…By setting a reasonable vibration coefficient and orthogonal coefficient, the mode with the highest sensitivity to cracks is selected for crack detection. …”
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Empowering Quality of Recommendations by Integrating Matrix Factorization Approaches With Louvain Community Detection by Srilatha Tokala, Murali Krishna Enduri, T. Jaya Lakshmi, Ashu Abdul, Jenhui Chen

“…Owing to the expanding size of the dataset and as the complexity increases, there arises an issue in delivering accurate recommendations to the users. …”
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Partial feature reparameterization and shallow-level interaction for remote sensing object detection by Minh Tai Pham Nguyen, Quoc Duy Nam Nguyen, Hoang Viet Anh Le, Minh Khue Phan Tran, Tadashi Nakano, Thi Hong Tran

“…Abstract Remote sensing object detection has recently emerged as one of the challenging topics in the field of deep learning applications due to the demand for both high detection performance and computational efficiency. …”
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Novel Wavelet Convolutional Neural Networks for Signal Detection in OFDM-IM Systems by Yang Zhao, SI-YU Zhang, Yuexia Zhang, Gongpu Wang, Behnam Shahrrava

“…However, CNNs' limited receptive field growth poses a challenge in capturing long range dependencies. To achieve efficient deep learning based OFDM-IM detection, this paper proposes two novel OFDM-IM signal detection networks that integrate wavelet transforms with CNNs (WTConv). …”
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Sports video temporal action detection technology based on an improved MSST algorithm by Lai Lixin, Fang Yu

“…Sports videos contain a large number of irrelevant backgrounds and static frames, which affect the efficiency and accuracy of temporal action detection. …”
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BDK-YOLOv8: An Enhanced Algorithm for UAV Infrared Image Object Detection by Nan Xiao, Xianggong Hong, Zixuan Zheng

“…Finally, channel pruning is applied to reduce model parameters and computational complexity, improving detection efficiency.Experimental results show that the proposed algorithm achieves 94.3% mAP50 on the HIT-UAV dataset, a 1.6% improvement over the original YOLOv8n, with a 3% increase in recall. …”
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