IEEE

Self-Supervised Learning-For Underwater Acoustic Signal Classification With Mixup

Abstract: Underwater acoustic signal classification is a critical task that involves identifying different types of signals in a complex and dynamic underwater environment, which is often contaminated ...
IT-Online

Data Scientist (Python, Machine Learning, LLMs) – (In Office) CPT – Western Cape Cape Town

ENVIRONMENT: An Investment company is searching for a talented and driven Data Scientist to join their innovative and growing team based in Durbanville, Cape Town. This is an exciting opportunity to ...
IEEE

Self-Supervised Generalized Zero Shot Learning for Medical Image Classification Using Novel Interpretable Saliency Maps

Abstract: In many real world medical image classification settings, access to samples of all disease classes is not feasible, affecting the robustness of a system expected to have high performance in ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
GitHub

Bootstrap Your Own Latent (BYOL), in Pytorch

Practical implementation of an astoundingly simple method for self-supervised learning that achieves a new state of the art (surpassing SimCLR) without contrastive learning and having to designate ...
EurekAlert!

A review of machine learning advances in reliability-based design, integrity assessment, inspection and maintenance of pipelines

A systematic review newly published in the Journal of Pipeline Science and Engineering maps machine learning (ML) advances for pipelines across the full lifecycle: reliability-based design, structural ...