Results 1 to 10 of about 6,846,537 (251)

A General Approach for Achieving Supervised Subspace Learning in Sparse Representation

IEEE Access, 2019
Over the past few decades, a large family of subspace learning algorithms based on dictionary learning have been designed to provide different solutions to learn subspace feature.
Jianshun Sang, Dezhong Peng, Yongsheng Sang   +2 more
doaj   +1 more source

Supervised methods of machine learning for email classification: a literature survey

Systems Science & Control Engineering
In today’s digital landscape, email is acknowledged as a critical conduit for global data exchanges. With a surge in data volume, malefactors exploit user identities, leading to data misuse.
Muath AlShaikh, Yasser Alrajeh, Sultan Alamri, Suhib Melhem, Ahmed Abu-Khadrah   +4 more
doaj   +1 more source

A survey of the impact of self-supervised pretraining for diagnostic tasks in medical X-ray, CT, MRI, and ultrasound

BMC Medical Imaging
Self-supervised pretraining has been observed to be effective at improving feature representations for transfer learning, leveraging large amounts of unlabelled data.
Blake VanBerlo, Jesse Hoey, Alexander Wong   +2 more
doaj   +1 more source

On Leveraging Machine Learning in Sport Science in the Hypothetico-deductive Framework

Sports Medicine - Open
Supervised machine learning (ML) offers an exciting suite of algorithms that could benefit research in sport science. In principle, supervised ML approaches were designed for pure prediction, as opposed to explanation, leading to a rise in powerful, but ...
Jordan Rodu, Alexandra F. DeJong Lempke, Natalie Kupperman, Jay Hertel   +3 more
doaj   +1 more source

Do more with less: Exploring semi-supervised learning for geological image classification

Applied Computing and Geosciences
Labelled datasets within geoscience can often be small, with data acquisition both costly and challenging, and their interpretation and downstream use in machine learning difficult due to data scarcity.
Hisham I. Mamode, Gary J. Hampson, Cédric M. John   +2 more
doaj   +1 more source

Global reconstruction of 3D flow field based on 2D local masked self-supervision

Kongqi donglixue xuebao
Flow field reconstruction is of great value in engineering applications such as super-resolution reconstruction and inversion of experimental fluid mechanics.
Zhixiang Xu, Xuesen Chu, Xuesen Chu
doaj   +1 more source

Investigating Contrastive Pair Learning’s Frontiers in Supervised, Semisupervised, and Self-Supervised Learning

Journal of Imaging
In recent years, contrastive learning has been a highly favored method for self-supervised representation learning, which significantly improves the unsupervised training of deep image models. Self-supervised learning is a subset of unsupervised learning
Bihi Sabiri, Amal Khtira, Bouchra El Asri, Maryem Rhanoui   +3 more
doaj   +1 more source

Enhancing Software Defect Prediction Using Ensemble Techniques and Diverse Machine Learning Paradigms

Eng
In today’s fast-paced world of software development, it is essential to ensure that programs run smoothly without any issues. When dealing with complex applications, the objective is to predict and resolve problems before they escalate. The prediction of
Ayesha Siddika, Momotaz Begum, Fahmid Al Farid, Jia Uddin, Hezerul Abdul Karim   +4 more
doaj   +1 more source

Contrastive Self-Supervised Learning for Sensor-Based Human Activity Recognition: A Review

IEEE Access
Deep learning models have achieved significant success in human activity recognition, particularly in assisted living and telemonitoring. However, training these models requires substantial amounts of labeled training data, which is time-consuming and ...
Hui Chen, Charles Gouin-Vallerand, Kevin Bouchard, Sebastien Gaboury, Melanie Couture, Nathalie Bier, Sylvain Giroux   +6 more
doaj   +1 more source

A review of distinct machine learning classifiers for healthcare fraud detection

Journal of Big Data
Healthcare insurance fraud is a major problem, with an estimated $300 billion lost annually in the United States. Machine learning has been explored as a tool for fraud detection for over a decade, but challenges remain, including class imbalance ...
Ethan D. Curtis, Preston Billion-Polak, Taghi M. Khoshgoftaar, Borko Furht   +3 more
doaj   +1 more source