Fusing Equivalent Circuit Models and Explainable Machine Learning for Internal Short Circuit Diagnosis in Lithium‐Ion Batteries

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Comparative Evaluation of Deep Learning Models for Diagnosis of COVID-19 Using X-ray Images and Computed Tomography

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Improving land cover change modelling with machine learning: a comparative analysis of SVM and XGBoost in the Lesotho Lowlands

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Enhancing BIM Modeling Ability of Undergraduate Architectural Engineering Students through the Integration of Flipped Classroom and Collaborative Learning

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Modelling the Livelihood Vulnerability Index (LVI-IPCC) with Machine Learning in Agro-Ecological Region I of Southern Zambia

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Epidemic Forecasting via Hybrid Deep Learning With Unified Visibility and Temporal Graphs Under Stochastic Noise Modelling

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Development of machine learning models for predicting early pregnancy outcomes based on β-hCG, progesterone, and estradiol

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A model for music emotion recognition and aesthetic education effect evaluation based on deep learning and multimodal data

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Data-driven analysis and prediction of traffic accident dynamics using spatiotemporal modeling and optimized machine learning techniques

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Corrections to “Internet of Things (IoT) and Machine Learning Model of Plant Disease Prediction–Blister Blight for Tea Plant”

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Api based automated plant disease analysis using transfer learning on pre-trained vision transformer model

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Modeling Pedestrian Priority at Unsignalized Crossings Using Machine Learning: Toward Data-Driven Transport Policy Solutions

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Predictive divergence in machine learning models for clinical mortality risk: A multicohort study of covid-19 patients

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The evolution of open educational practices: a comparative analysis of models and a new framework for the AI era

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Efficient Knowledge Deletion from Trained Models Through Layer-wise Partial Machine Unlearning

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Exponential Family Graphical Models: Correlated Replicates and Unmeasured Confounders, with Applications to fMRI Data

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Availability prediction of solar water pumping system through stochastic modeling and nature-inspired algorithms

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Efficient Knowledge Deletion from Trained Models Through Layer-wise Partial Machine Unlearning

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Exponential Family Graphical Models: Correlated Replicates and Unmeasured Confounders, with Applications to fMRI Data

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Efficient Knowledge Deletion from Trained Models Through Layer-wise Partial Machine Unlearning

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