2025年2月10日 · Linear Discriminant Analysis (LDA) also known as Normal Discriminant Analysis is supervised classification problem that helps separate two or more classes by converting …

2024年11月10日 · 本文将重点探讨如何利用OpenCV实现线性判别分析（LDA）算法，并应用于图像特征提取，从而提升图像识别的准确性和效率。 线性判别分析（LDA）是一种经典的监督 …

2005年4月1日 · This paper proposes an innovative algorithm named 2D-LDA, which directly extracts the proper features from image matrices based on Fisher’s Linear Discriminant …

This article describes, through a simple example, usage of a Linear Discriminant Analysis (LDA) technique to classify particles in an image. We start with a very simple, almost pre-segmented, …

2019年11月10日 · In this article, we discovered the topic modeling for images and how we can use the image caption dataset to build the topic detection model. Specifically, we built the topic …

2013年4月5日 · Two new extensions of latent Dirichlet allocation (LDA), denoted topic-supervised LDA (ts-LDA) and class-specific-simplex LDA (css-LDA), are proposed for image classification.

2009年9月4日 · We use our presented symmetrical invariant LBP (SILBP) texture descriptor to extract image visual features. We then explored effectiveness of principal component analysis …

This repository contains the implementation of an image-based LDA model for use in semi-automation of the image annotation and data curation process. It uses unsupervised Latent …

2013年5月12日 · 本文是 LDA学习笔记 系列文章的第5部分，主要介绍LDA在图像分类中的应用。 图像处理问题的第一步是特征提取，本文介绍的特征提取算法是 SIFT (Scale-Invariant …

Abstract—Two new extensions of latent Dirichlet allocation (LDA), denoted topic-supervised LDA (ts-LDA) and class-specific-simplex LDA (css-LDA), are proposed for image classification.