Frontiers

Profiling investor behavior in the Malaysian derivatives market using K-means clustering

1 Department of Applied Sciences, Intelligent Asset Reliability Centre, Institute of Emerging Digital Technologies, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia 2 Bursa Malaysia Berhad, ...
Frontiers

Profiling Investor Behavior in the Malaysian Derivatives Market Using K-Means Clustering

The final, formatted version of the article will be published soon. This study investigates the trading behaviors of Malaysian derivatives traders using a comprehensive dataset from Bursa Malaysia ...
GitHub

Used Unsupervised Machine Learning using KMeans for user segmentation of mall customers dataset.

There was an error while loading. Please reload this page. This project demonstrates how to build a K-Means clustering algorithm from scratch to segment mall ...
Scientific Research Publishing

From U-Net to Swin-Unet Transformers: The Next-Generation Advances in Brain Tumor Segmentation with Deep Learning ()

Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...
News Medical

New AI model performs medical image segmentation with far less data

A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...
GitHub

mall-customer-segmentation

A mall customer segmentation machine learning model categorizes customers based on their behaviors and preferences, enabling businesses to tailor marketing strategies and optimize operations for ...
PC World

This built-in Windows 11 app can pull the text in any image with one click

Microsoft has added an OCR function (Optical Character Recognition) to the Windows Photos app, which basically means it can now recognize text in an image and instantly extract it for you. To use this ...
Scientific Research Publishing

Ng, H.P., Ong, S.H., Foong, K.W.C., Goh, P.S. and Nowinski, W.L. Medical Image Segmentation Using K-Means Clustering and Improved Watershed Algorithm. 2006 IEEE Southwest ...

ABSTRACT: Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering ...
IEEE

K-means Clustering for Image Segmentation Using Approximate Booth Multiplier

Abstract: K-means clustering is an unsupervised learning algorithm that assigns unlabeled data to different clusters depending on the similarity rather than predefined labels. It finds application in ...