Ophthalmology Times

Study finds mixed real and synthetic eye images enhance ocular AI performance

Training a computer vision model on a 50:50 blend of synthetic and real eye images produces more reliable segmentation of the ...
Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
LinkedIn

Customer Segmentation with K-Means and Hierarchical Clustering

Recently completed a project using unsupervised learning to uncover insights from customer data, focusing on segmentation based on annual income, spending score. Aim was to identify meaningful groups ...
Nature

A novel approach for the segmentation of retinal images by integration K-means clustering algorithm with graph cut for image segmentation

The primary resultant of Diabetes and key cause of vision loss is DR. For prompt intervention and efficient management of DR, early diagnosis and precise segmentation of retinal lesions are essential.
GitHub

alam025/customer-segmentation-kmeans-clustering

Advanced K-Means clustering system for customer analytics and segmentation using machine learning. Includes RFM analysis, business insights, and actionable marketing strategies. - ...
IEEE

Optimizing Thermal Image Segmentation Using K-Means Clustering and Morphological Operations for Photovoltaic

Abstract: Thermal imaging has become a critical tool in the diagnosis and maintenance of photovoltaic (PV) panels, particularly in detecting localized hotspots that indicate underlying faults. We ...
GitHub

Customer Segmentation with K-Means Clustering

In this project, I explored the Mall_Customers.csv dataset with the main focus on customer segmentation using K-Means clustering. The goal was to identify distinct customer groups based on Age, Annual ...
Nature

Hyperspectral imaging and K-means clustering for material structure classification and detection of unmanned aerial vehicles

Unmanned aerial vehicles (UAVs) have become increasingly widespread in a variety of industries due to their versatility and efficiency in applications such as agriculture, surveillance, logistics, and ...
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 ...
Scientific Research Publishing

Tabianan, K., Velu, S. and Ravi, V. (2022) K-Means Clustering Approach for Intelligent Customer Segmentation Using Customer Purchase Behavior Data. Sustainability, 14, Article ...

ABSTRACT: Doping is an issue associated with elite sports as athletes attempt to enhance their performance to gain an edge over other athletes. However, the prevalence of doping is continuously ...
TWCN Tech News

How to upscale Image using Copilot PC?

In this tutorial, we will show you how to upscale an image using Copilot PC. Whether you want to take a large print of a picture, improve old photos, or crop a photo to focus on the content, you can ...
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 ...