Directions Magazine

Machine Learning in Gis

Machine learning in GIS gives a Geographic information system the ability to detect patterns, classify features, and support faster decision-making from geographic data and information. In practice, ...
Frontiers

A machine learning-based classification model for interstitial lung disease in rheumatoid arthritis

This study aimed to develop and validate a preliminary classification and diagnostic model for rheumatoid arthritis-associated interstitial lung disease (RA-ILD) using routine, readily available ...
Fast Company

MIT researchers just mapped New York City foot traffic for the first time ever

New York City is a city of walkers. More trips are made on foot than by car (41% versus 28%) and the city’s “80X50” climate action plan envisions that 80% of all trips by 2050 will be made either on ...
IEEE

An Approach to Attack Classification for Programmable Network Infrastructure Using Machine Learning and Deep Learning Solutions

Abstract: The rapid development of Internet-connected devices has driven the rise of smart cities, where large-scale Internet of Things (IoT) systems require efficient infrastructure management with ...
Beebom

AI vs Machine Learning: What is the Difference?

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
Scientific Research Publishing

Performance of Different Machine Learning Algorithms for Credit Risk Classification ()

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
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 ...
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 = ...
IEEE

Machine Learning Techniques to Improve the Cognitive Workload Classification Using Multimodal Sensors’ Data

Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...