We analyzed Philly street scenes and identified signs of gentrification using machine learning trained on longtime residents’ observations

Researchers are using machine learning models to identify gentrification in imagery. Community insights help keep the models ...
Frontiers

Traditional machine learning in biomedical image analysis: before you go too deep

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...
Scientific Research Publishing

Liu, L. (2024) Machine Learning-Driven Corrosion Detection and Classification in Pipelines. Ph.D. Thesis, University of Wales Trinity Saint David.

ABSTRACT: Corrosion is one of the most challenging problems that affects the safety and durability of onshore pipelines. Corrosion-resistant steels play a pivotal role in ensuring long lasting ...
IEEE

Federated Learning for Medical Image Classification: A Comprehensive Benchmark

Abstract: The federated learning (FL) paradigm is well-suited for the field of medical image analysis, as it can effectively cope with machine learning on isolated multi-center data while protecting ...
The New York Times

48 Hours Without A.I.

It’s everywhere, as the author learned the hard way while making as little contact as possible with machine learning and generative artificial intelligence. It’s everywhere, as the author learned the ...
GitHub

Azure AutoML for Images - Image Classification

This repository contains Python notebooks demonstrating image classification using Azure AutoML for Images. These notebooks provide practical examples of building computer vision models for various ...
Visual Studio Magazine

Tsetlin Machine Binary Classification Using C#

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
Visual Studio Magazine

Predicting the Future Using Azure Machine Learning

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...
PNAS

Adaptable microplastic classification using similarity learning on µFTIR spectra collected from µFTIR focal plane array imaging

Microplastics have been found to be highly pervasive in the environment, driving concerns for health, environment, and ecology. Analytical methods that can accurately identify microplastics are ...
IEEE

Analysis of Image Classification Using Machine Learning Approach

Abstract: Among the technologies that are utilized in the research and development of contemporary science and technology, image classification is an essential technology. Scholars from a variety of ...