Machine Learning-Based Computer Vision for Depth Camera-Based Physiotherapy Movement Assessment: A Systematic Review by Yafeng Zhou, Fadilla ’Atyka Nor Rashid, Marizuana Mat Daud, Mohammad Kamrul Hasan, Wangmei Chen

Subjects: “…computer vision…”
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Automatic detection and classification of drill bit damage using deep learning and computer vision algorithms by Xiongwen Yang, Xiao Feng, Chris Cheng, Jiaqing Yu, Qing Zhang, Zilong Gao, Yang Liu, Bo Chen

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AI powered detection and assessment of onychomycosis: A spotlight on yellow and deep learning by C. Agostini, R. Ranjan, M. Molnarova, A. Hadzic, O. Kubesch, V. Schnidar, H. Schnidar

“…Abstract Background Despite significant advances in computer‐aided diagnostics, onychomycosis, a widespread fungal nail infection, lacks an automated approach for objective analysis and classification. …”
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Preliminary Electroencephalography-Based Assessment of Anxiety Using Machine Learning: A Pilot Study by Katarzyna Mróz, Kamil Jonak

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Machine Learning Using Approximate Computing by Padmanabhan Balasubramanian, Syed Mohammed Mosayeeb Al Hady Zaheen, Douglas L. Maskell

“…This work analyzes the application of approximate computing for machine learning, specifically focusing on k-means clustering, one of the more widely used unsupervised machine learning algorithms. …”
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On Risk Assessment for Out-of-Distribution Detection by Anton Vasiliuk

Subjects: “…Computer vision…”
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A Computer-Aided Approach to Canine Hip Dysplasia Assessment: Measuring Femoral Head–Acetabulum Distance with Deep Learning by Pedro Franco-Gonçalo, Pedro Leite, Sofia Alves-Pimenta, Bruno Colaço, Lio Gonçalves, Vítor Filipe, Fintan McEvoy, Manuel Ferreira, Mário Ginja

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Assessing seventh-grade students' computational thinking skills through problem-based learning: Focus on integer addition and subtraction by Hapizah Hapizah, Anadia Muli Mariela, Budi Mulyono

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Assessing the Impact of Prior Coding and Artificial Intelligence Learning on Non-Computing Majors’ Perception of AI in a University Context by Yong-Jik Lee, Robert O. Davis

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Grapevine inflorescence segmentation and flower estimation based on Computer Vision techniques for early yield assessment by Germano Moreira, Filipe Neves dos Santos, Mário Cunha

“…The number of inflorescences and flowers per vine is one of the main components and their assessment serves as an early predictor, which can explain up to 85-90% of yield variability. …”
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Leveraging foundation models and goal-dependent annotations for automated cell confluence assessment by Maximilian Josef Joas, Daniel Freund, Robert Haase, Erhard Rahm, Jan Ewald

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Design and Production of Interactive E-Learning Content Based on Need Assessment and its Impact on Self-Regulation Learning and Academic Performance of Pharmacy Students by Bahram Rostami, Parvin Zolghadri, Mansour Ojaghloo, Karimi Moghaddam, Alireza Yazdinezhad, Fahime Khaleghi

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Develoment of The Computer Simulation of Oscillation in Physics Learning by Y Sumardi, A F Amalia, U N Prabowo

“…This research aimed to develop the computer simulation of oscillation in physics learning by using MATLAB. …”
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Research on ischemic stroke risk assessment based on CTA radiomics and machine learning by Zhi-Li Li, Hong-Yu Yang, Xiao-Xiao Lv, Ya-Kun Zhang, Xin-Yu Zhu, Yu-Rou Zhang, Li Guo

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Assessing land degradation in lower gangetic west bengal using GIS-based soft computing and advanced machine learning algorithms by Gopal Chowdhury, Ashis Kumar Saha

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Working on Critical Thinking skills using the computer lab works of an Engineering subject by Juan Giner-Navarro, Águeda Sonseca, José Martínez-Casas, Javier Carballeira

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Auto-Segmentation via deep-learning approaches for the assessment of flap volume after reconstructive surgery or radiotherapy in head and neck cancer by Juliette Thariat, Zacharia Mesbah, Youssef Chahir, Arnaud Beddok, Alice Blache, Jean Bourhis, Abir Fatallah, Mathieu Hatt, Romain Modzelewski

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Advances in Composite Power System Reliability Assessment: Trends and Machine Learning Role by Chiranjeevi Yarramsetty, Tukaram Moger, Debashisha Jena, Veeranki Srinivasa Rao

“…A comparative examination of conventional and Machine Learning (ML)-based methods demonstrates that deep learning models, such as Convolutional Neural Networks, offer substantial reductions in computational time while maintaining reliability assessment precision. …”
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New Predictive Models for the Computation of Reinforced Concrete Columns Shear Strength by Anthos I. Ioannou, David Galbraith, Nikolaos Bakas, George Markou, John Bellos

“…Significantly improved predictive models are proposed herein through the implementation of machine learning (ML) algorithms on refined datasets. Three ML models, LREGR, POLYREG-HYT, and XGBoost-HYT-CV, were used to develop different predictive models that were able to compute the shear strength of RC columns. …”
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Gamified Diagnostic Assessment Using Quizizz: Investigating Motivation and Perceptions of Indonesian ESL Students by Laili Inayatus Sholihah, Delsa Miranty

Subjects: “…computer-assisted language learning (call)…”
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