eLife

Distinct involvements of the subthalamic nucleus subpopulations in reward-biased decision-making in monkeys

The subthalamic nucleus contains subpopulations with different contributions to deliberative decision-making based on noisy evidence and reward-driven preferences.
C&EN

Conserved Water Networks Identification for Drug Design Using Density Clustering Approaches on Positional and Orientational Data

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Article Views are the COUNTER-compliant sum of full text article downloads since ...
IEEE

K-means Clustering Solution for Image Compression

Abstract: The paper presents a detailed research study of the k-means clustering algorithm to be used for image compression tasks, where the RGB values of the colors are considered XYZ coordinates of ...
GitHub

kkahol-toronto/agent-clustering

Introduction This document outlines the technical specifications for a two-agent system designed to perform automated clustering analysis, iterative evaluation, hyperparameter optimization, scheduled ...
Visual Studio Magazine

DBSCAN Data Clustering from Scratch Using C#

Compared to other clustering techniques, DBSCAN does not require you to explicitly specify how many data clusters to use, explains Dr. James McCaffrey of Microsoft Research in this full-code, ...
GitHub

Easy-to-Use Apple Vision wrapper for text extraction and clustering

apple_ocr is a utility for Optical Character Recognition (OCR) that facilitates the extraction of text from images. This Python-based tool is designed to help developers, researchers, and enthusiasts ...
Scientific Research Publishing

Maternal and Child Health Care Quality Assessment: An Improved Approach Using K-Means Clustering ()

1 Department of Communication Science and Engineering, Nelson Mandela Institution of Science and Technology, Arusha, Tanzania. 2 School for Information Sciences, Center for Information and Systems, ...
IEEE

K-means clustering algorithm and Python implementation

Abstract: K-means is a commonly used algorithm in machine learning. It is an unsupervised learning algorithm. It is regularly used for data clustering. Only the number of clusters are needed to be ...