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Articles by Mitchell TM
Learner emotion classification in online English instruction based on multimodal analysis
With the deep integration of globalization and artificial intelligence technologies, online education has evolved from a supplementary instructional approach into an increasingly important component of the modern educational ecosystem.
Optimizing PROAFTN classifier with ant colony algorithm: enhanced diabetes detection benchmarking
Classification is a fundamental aspect of machine learning (ML) and artificial intelligence (AI), focusing on building reliable models to uncover complex patterns in data. The ultimate goal is to accurately assign unseen instances to predefined categories, which makes classification a vital tool for automating the decision-making process and effectively managing data (Bishop, 2006; Friedman, Hastie & Tibshirani, 2001; Kotsiantis, Zaharakis & Pintelas, 2007).
Sequence-based undersampling: an algorithm for managing imbalanced datasets
The training and testing procedure is aimed to mimicry meteorological operations in the QPE field. Thus, we train with 1 month worth of radiometer-radar data and use the trained net to estimate the precipitation in the following month using the radiometers only.
Research on furniture image classification based on MobileNetNAK
Image classification, a fundamental and essential task in computer vision, seeks to precisely recognize and categorize the elements within an image using algorithmic models (Binder, Müller & Kawanabe, 2012). As technology continues to evolve, this technique has found extensive applications across numerous domains, significantly contributing to the advancement of intelligent systems (Chen et al., 2021).
Seasonal mouse cadaver microbial study: rupture time and postmortem interval estimation model construction
Seasonal mouse cadaver microbial study: rupture time and postmortem interval estimation model construction 1Institute of Forensic Science, Ministry of Public Security, Beijing, China 2Key Laboratory of Forensic Genetics of Ministry of Public Security, Beijing, China 3Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, Hunan, China 4College of Life Sciences,, Nanjing Agricultural University, Nanjing, Jiangsu, China DOI 10.7717/peerj.17932...
ShallowBKGC: a BERT-enhanced shallow neural network model for knowledge graph completion
Knowledge graphs (KGs) such as DBpedia (Auer et al., 2007), Freebase (Bollacker et al., 2008), NELL (Carlson et al., 2010), and Wikidata (Vrandečič & Krötzsch, 2014) are important resources for many artificial intelligence tasks including semantic search (Feddoul, 2020), recommendations (Wu et al., 2022) and question answering (Li & Moens, 2022). These KGs are composed of factual triplets, with each triplet (h,r,t) denotes the fact that relation r exists between head entity h and tail entity t.
Deep learning-based method for sentiment analysis for patients’ drug reviews
Deep learning-based method for sentiment analysis for patients’ drug reviews 1Institute of Informatics, Faculty of Science and Informatics, University of Szeged, Szeged, Hungary 2Computer Science Department, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom 3DAAI Researsh Group, College of Computing and Digital Technology, Birmingham City University, Birmingham, United Kingdom 4Computer Science Department, College of Computer and Information Sciences,...
A novel approach for explicit song lyrics detection using machine and deep ensemble learning models
In recent years, music has become one of the most prevalent forms of entertainment, recreation, and information. The digital music collection is growing rapidly, as artists express themselves through lyrics. However, some lyrics contain content that is not suitable for young listeners, such as references to sexual, violent, or drug-related themes. This can have negative effects on young people (Arnett, 1991; Ballard & Coates, 1995).
A space and time efficient convolutional neural network for age group estimation from facial images
Introduction Facial images possess various characteristics such as age, gender, expression, social status, and ethnicity (Alley, 2013). If these features are accurately estimated, they can be utilized in numerous domains ranging from social life to technology. It is crucial to employ these facial features with scientific methods and apply them in real applications and commercial areas.
COVID-19 mortality prediction using ensemble learning and grey wolf optimization
Support vector machines Support vector machines (SVM) (Cortes & Vapnik, 1995) is one of the most robust supervised learning algorithms. SVM was first developed to address binary classification tasks before being expanded to cover multi-class classification issues. The SVM’s main idea is to construct a n-dimensional hyperplane where n is the number of variables involved. The hyperplane is optimized to maximize the distance between the two farthest data points of two or more classes.
Self-aware cycle curriculum learning for multiple-choice reading comprehension
A Further explanation of empirical-based method The empirical-based approach is entirely manual-based. In Table A.1, the type of question is ‘matching’, and the answer can be obtained from this sentence ‘The gas price will be changed again tomorrow’ in the text. This type of question is usually simple. In Table A.2, the question type is ‘linguistic’. This type of question usually requires understanding the whole document, which is more difficult than the ‘matching’ type.
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