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 ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New ...

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

Contrastive self-supervised learning for neurodegenerative disorder classification

Neurodegenerative diseases such as Alzheimer's disease (AD) or frontotemporal lobar degeneration (FTLD) involve specific loss of brain volume, detectable in vivo using T1-weighted MRI scans.
Frontiers

Weakly supervised learning in thymoma histopathology classification: an interpretable approach

Thymoma classification is challenging due to its diverse morphology. Accurate classification is crucial for diagnosis, but current methods often struggle with complex tumor subtypes. This study ...
Techopedia

Supervised Learning

Margaret Rouse is an award-winning technical writer and teacher known for her ability to explain complex technical subjects simply to a non-technical, business audience. Over… Supervised learning ...
IEEE

Self-Supervised Learning Malware Traffic Classification Based on Masked Autoencoder

Abstract: Malware traffic classification (MTC) is one of the important techniques to ensure the security of cyberspace, which aims to detect anomalies and classify different types of network traffic.
eLife

DeepEthogram, a machine learning pipeline for supervised behavior classification from raw ...

Videos of animal behavior are used to quantify researcher-defined behaviors of interest to study neural function, gene mutations, and pharmacological therapies. Behaviors of interest are often scored ...