A visual positioning method for tunnel boring machines in underground coal mines based on anchor net features by Xuhui ZHANG, Yunkai CHI, Yuyang DU, Junying JIANG, Wenjuan YANG, Youjun ZHAO, Jicheng WAN, Yanqun WANG, Chenhui TIAN

“…The proposed method yielded a maximum error of 163 mm, indicating a 23.5% reduction compared to the 213 mm obtained using the PL-VINS algorithm. …”
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Traversability Analysis and Path Planning for Autonomous Wheeled Vehicles on Rigid Terrains by Nan Wang, Xiang Li, Zhe Suo, Jiuchen Fan, Jixin Wang, Dongxuan Xie

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High-Precision Stored-Grain Insect Pest Detection Method Based on PDA-YOLO by Fuyan Sun, Zhizhong Guan, Zongwang Lyu, Shanshan Liu

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Contextual information based anomaly detection for multi-scene aerial videos by Girisha S, Ujjwal Verma, Manohara M M. Pai, Radhika M. Pai

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An exact implementation of the generalized Zhang-Zhu criterion for elasto-plastic finite element calculations by Lianjin Tao, Linkun Huang, Xu Zhao, Johan Clausen, Qi Zhang, Boyang Jiao, Hehua Zhu

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A neuronal imaging dataset for deep learning in the reconstruction of single-neuron axons by Liya Li, Liya Li, Ying Hu, Ying Hu, Xiaojun Wang, Pei Sun, Tingwei Quan

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Bioinformatic identification of signature miRNAs associated with fetoplacental vascular dysfunction in gestational diabetes mellitus by Yulan Lu, Chunhong Liu, Xiaoxia Pang, Xinghong Chen, Chunfang Wang, Huatuo Huang

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Quality Assessment of MRI-Radiomics-Based Machine Learning Methods in Classification of Brain Tumors: Systematic Review by Shailesh S. Nayak, Saikiran Pendem, Girish R. Menon, Niranjana Sampathila, Prakashini Koteshwar

“…Various imaging modalities, including MRI, PET/CT, and advanced techniques like ASL and DTI, were utilized to extract radiomic features for analysis. Machine learning algorithms such as deep learning networks, support vector machines, random forests, and logistic regression were applied to develop predictive models. …”
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A Transformer-Based Approach for Efficient Geometric Feature Extraction from Vector Shape Data by Longfei Cui, Xinyu Niu, Haizhong Qian, Xiao Wang, Junkui Xu

“…Traditional methods rely on different machine learning algorithms tailored to specific types of line and polygon elements, limiting their general applicability. …”
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Assessment of pulmonary embolism probability using a machine learning model by D. V. Gavrilov, A. E. Andreichenko, A. D. Ermak, T. Yu. Kuznetsova, A. V. Gusev

“…Seven machine learning algorithms were applied to diagnose pulmonary embolism: XGBoost, LightGBM, CatBoost, Logistic Regression, MLP Classifier, Random Forest Classifier, Gradient Boosting Classifier.Results. …”
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From genetic data to kinship clarity: employing machine learning for detecting incestuous relations by Dejan Šorgić, Aleksandra Stefanović, Mladen Popović, Dušan Keckarević

“…Several machine learning algorithms and neural networks were tested for classification accuracy.Results:The CatBoost algorithm performed best in the binary classification of Normal Paternity vs. …”
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Research progress on intelligent coal caving theory and technology by WANG Jiachen, YANG Shengli, LI Lianghui, ZHANG Jinwang, WEI Weijie

“…This paper reviews the research progress on the "Four elements" coal caving theory, the relationship between the top coal recovery rate and the rock mixed ratio, a recovery rate prediction model based on block distribution, and the relationship between instantaneous rock mixed ratio and cumulative rock mixed ratio. …”
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Capturing Preferences of New Users in Generative Tasks with Minimal Interactions Collaborative Filtering Using Siamese Networks and Soft Clustering by Subharag Sarkar, Manfred Huber

“…Prediction of user preferences is a challenge, in particular when the objective is to learn them without requiring the user to provide a profile or a significant number of interactions. …”
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Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data. by Enrico Glaab, Jaume Bacardit, Jonathan M Garibaldi, Natalio Krasnogor

“…Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. …”
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A Parts Detection Network for Switch Machine Parts in Complex Rail Transit Scenarios by Jiu Yong, Jianwu Dang, Wenxuan Deng

“…However, in the detection of complex rail transit switch machine parts such as augmented reality and automatic inspection, existing algorithms have problems such as insufficient feature extraction, large computational complexity, and high demand for hardware resources. …”
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Optimal Scheduling of Biomass-Hybrid Microgrids with Energy Storage: An LSTM-PMOEVO Framework for Uncertain Environments by Zichong Wang, Yingying Zheng

“…Finally, a public dataset was utilized for the experiments to verify the performance of the proposed algorithm. Comparisons and discussions show that the proposed optimization strategies significantly improve the performance of PMOEVO, demonstrating marked advantages over six classical algorithms. …”
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MobileNetV3: an efficient deep learning-based feature selection and classification technique for cardiovascular disease by B. Dhanalaxmi, B. Naveen Kumar, Yeligeti Raju, Rama Seshagiri Rao Channapragada

“…Unfortunately, most currently utilized cardiovascular disease prediction algorithms could not achieve higher accuracy due to inadequate forecasting methodology and data-recognized techniques. …”
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Deep learning object detection-based early detection of lung cancer by Kuo-Yang Huang, Kuo-Yang Huang, Kuo-Yang Huang, Che-Liang Chung, Che-Liang Chung, Che-Liang Chung, Jia-Lang Xu

“…The performance of the You Only Look Once (YOLO) series of models in the lung CT image object detection task is compared in terms of algorithms, and different versions of YOLOv5, YOLOv8, YOLOv9, YOLOv10, and YOLOv11 are examined for lung cancer detection and classification. …”
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Dynamics of striatal action selection and reinforcement learning by Jack W Lindsey, Jeffrey Markowitz, Winthrop F Gillis, Sandeep R Datta, Ashok Litwin-Kumar

“…In our model, learning and action selection signals can be multiplexed without interference, enabling learning algorithms beyond those of standard temporal difference models.…”
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Baseline high-resolution maps of soil nutrients in Morocco to support sustainable agriculture by Yassine Bouslihim, Abdelkrim Bouasria, Ahmed Jelloul, Lotfi Khiari, Sara Dahhani, Rachid Mrabet, Rachid Moussadek

“…Uncertainty assessment through bootstrapping confirmed prediction stability across diverse agricultural landscapes. …”
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