Handwritten W-Net for High-Frequency Guided Single-Image Super-Resolution by Xiang Yang, Chen Fang, Xiaolan Xie, Minggang Dong

“…However, existing research has methodological limitations owing to the constraints posed by the model architecture and loss guidance used for optimization. …”
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Multi-Source Heterogeneous Data-Driven Digital Delivery System for Oil and Gas Surface Engineering by Wei Zhang, Zhixiang Dai, Taiwu Xia, Gangping Chen, Yihua Zhang, Jun Zhou, Cui Liu

“…To address the challenges of data fragmentation, inconsistent standards, and weak interactivity in oil and gas field surface engineering, this study proposes an intelligent delivery system integrated with three-dimensional dynamic modeling. Utilizing a layered collaborative framework, the system combines optimization algorithms and anomaly detection methods during data processing to enhance the relevance and reliability of high-dimensional data. …”
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Estimation of the Number of Active Sweat Glands Through Discrete Sweat Sensing by Jelte R. Haakma, Elisabetta Peri, Simona Turco, Eduard Pelssers, Jaap M. J. den Toonder, Massimo Mischi

“…Based on our findings, we provide recommendations for optimal device layouts to improve accuracy in estimating active sweat glands. …”
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Deep learning-based semantic segmentation with novel navigation line extraction for autonomous agricultural robots by Chijioke Leonard Nkwocha, Ning Wang

“…Then, we proposed a novel navigation line extraction algorithm based on the Douglas–Peucker algorithm which uses the output mask from the semantic segmentation to extract the centre navigation line for robot guidance. …”
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Dynamic-budget superpixel active learning for semantic segmentation by Yuemin Wang, Ian Stavness

“…A static budget could result in over- or under-labeling images as the number of high-impact regions in each image can vary.MethodsIn this paper, we present a novel dynamic-budget superpixel querying strategy that can query the optimal numbers of high-uncertainty superpixels in an image to improve the querying efficiency of regional active learning algorithms designed for semantic segmentation.ResultsFor two distinct datasets, we show that by allowing a dynamic budget for each image, the active learning algorithm is more effective compared to static-budget querying at the same low total labeling budget. …”
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Leveraging Feature Sets and Machine Learning for Enhanced Energy Load Prediction: A Comparative Analysis by Fernando Pedro Silva Almeida, Mauro Castelli, Nadine Côrte-Real

“…This study addresses the gap in existing research by comprehensively analyzing the performance of various machine learning algorithms, including ensemble learning and deep learning models, to improve prediction accuracy. …”
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Analysis of soil salinization and land use change under water conservation retrofit in the Hetao irrigation district by Yi Zhao, Shuya Yang, Haibin Shi, Haoqi Han, Yunlei Dong, Xianyue Li, Jianwen Yan, Yan Yan, Xu Dou, Feng Tian, Qingfeng Miao

“…After the water conservation retrofit, non-saline soil increased by 326.5 km2, indicating improved soil conditions. The overall accuracy of the Gradient Boosting Tree classification model is 95.00 % and the Kappa coefficient is 0.93, which is the optimal model for land use type classification. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…This study focuses on optimizing and comparing various machine learning models for ASD diagnosis, while incorporating explainable AI techniques to ensure model transparency and interpretability. …”
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Know your competitor! Analyzing and predicting the location of competing stores: The case study of Valora at Swiss railway stations by Thomas Wieland

“…Machine learning algorithms are used to check and optimize the predictive ability of the models. …”
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Contributions to the Development of Tetrahedral Mobile Robots with Omnidirectional Locomotion Units by Anca-Corina Simerean, Mihai Olimpiu Tătar

“…The second prototype is presented as an advanced and improved version of the first model, integrating significant modifications in both the structural design and the robot’s functionality. …”
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A deep contrastive learning-based image retrieval system for automatic detection of infectious cattle diseases by Veerayuth Kittichai, Morakot Kaewthamasorn, Apinya Arnuphaprasert, Rangsan Jomtarak, Kaung Myat Naing, Teerawat Tongloy, Santhad Chuwongin, Siridech Boonsang

“…The model’s performance was also improved by a fine-tuned procedure between k-nearest neighbor and its normalized distance of each data point, including precision of 0.833 ± 0.134, specificity of 0.930 ± 0.054, recall of 0.838 ± 0.118, and accuracy of 0.915 ± 0.025, respectively. …”
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Predictive framework of vegetation resistance in channel flow by Fengcong Jia, Weijie Wang, Yu Han, Jiayu Du, Yue Zhang, Zihan Liu, Hairong Gao

“…This study introduces a machine learning-based framework for predicting vegetation flow resistance, incorporating nine ML methods, including SVM, XGBoost, and BP. To improve predictive performance, optimization algorithms such as PSO, WSO, and RIME were applied. …”
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SCCA-YOLO: Spatial Channel Fusion and Context-Aware YOLO for Lunar Crater Detection by Jiahao Tang, Boyuan Gu, Tianyou Li, Ying-Bo Lu

“…In addition, the improved Channel Attention Concatenation (CAC) strategy adaptively learns channel-wise importance weights during feature concatenation, further optimizing multi-scale semantic feature fusion and enhancing the model’s sensitivity to critical crater features. …”
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An Elderly-Oriented Form Design of Low-Speed New Energy Vehicles Based on Rough Set Theory and Support Vector Regression by Zimo Chen

“…Second, the cars’ appearances are deconstructed by morphological analysis, and the key design features affecting elderly-oriented satisfaction are identified by a rough set attribute reduction algorithm. Finally, support vector regression is used to establish a mapping model of elderly-oriented Kansei factors and the key design features to predict the elderly-oriented form design of optimal low-speed NEVs. …”
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Automated Support Generation for Fixed Partial Dentures and Impact of Bone Loss, Bone Quality and Support Types: Parametric Cad and Finite Element Analysis by Hassen Jemaa, Michael Eisenburger, Andreas Greuling

“…<b>Background:</b> This study aimed to develop an algorithm for modelling tooth–tooth or implant–implant support configurations for a given 4-unit fixed partial denture (FPD). …”
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Economic Dispatch Analysis of Risk Prevention and Control Based on Game Theory Equilibrium by Qixiang WANG, Zhentao HAN, Yi LIANG

“…In order to solve these problems, this paper first proposes an economic dispatch mathematical model for risk prevention and control of the power system considering green power generation and consumption and then puts forward a game theory equilibrium solution algorithm based on the optimal response method. …”
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Cattle identification based on multiple feature decision layer fusion by Dongxu Li, Baoshan Li, Qi Li, Yueming Wang, Mei Yang, Mingshuo Han

“…The corresponding cattle IDs of these features are then processed using One-Hot encoding to serve as the final input for the decision layer, and various ensemble strategies are used to optimize the model. The results show that using the multimodal decision fusion method makes the recognition accuracy reach 95.74%, 1.4% higher than the traditional optimal unimodal recognition accuracy. …”
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Crowd Evacuation in Stadiums Using Fire Alarm Prediction by Afnan A. Alazbah, Osama Rabie, Abdullah Al-Barakati

“…This study introduces an AI-driven predictive fire alarm and evacuation model that leverages machine learning algorithms and real-time environmental sensor data to anticipate fire hazards before ignition, improving emergency response efficiency. …”
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3D Human Motion Capture Method Based on Computer Vision by A. D. Obukhov, D. L. Dedov, E. O. Surkova, I. L. Korobova

“…Based on the skeletal points obtained from the neural network, a three-dimensional reconstruction of the human body model was carried out using various triangulation algorithms.Results. …”
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An AIoT-Based Automated Farming Irrigation System for Farmers in Limpopo Province by Relebogile Langa, Michael Nthabiseng Moeti, Thabiso Maubane

“…A machine learning precipitation prediction algorithm optimizes water usage. The paper also describes a system with multiple sensors that detect soil parameters, and automatically irrigate land based on soil moisture by switching the motor on/off. …”
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