Nature

A deep dictionary clustering approach for unsupervised image retrieval using convolutional sparse coding

Medical image repositories have been rapidly growing due to the widespread use of imaging techniques, making manual annotation unfeasible. Efficient image retrieval systems are crucial for diagnosing ...
BizTech

What Are the Benefits of Unsupervised Machine Learning and Clustering?

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...
Science Daily

Novel machine learning-based cluster analysis method that leverages target material property

Conventional clustering techniques often focus on basic features like crystal structure and elemental composition, neglecting target properties such as band gaps and dielectric constants. A new study ...
Nature

Cluster-based histopathology phenotype representation learning by self-supervised multi-class-token hierarchical ViT

Access to large-scale and good quality dataset is a primary driver in machine learning, with well-known datatsets such as ImageNet 1 in computer vision has led to remarkable achievements in the domain ...
Visual Studio Magazine

Clustering Mixed Categorical and Numeric Data Using k-Means with C#

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a "very tricky" machine learning technique. Data clustering is the process of grouping data items together so ...