Texture Classification
31 papers with code • 0 benchmarks • 5 datasets
Texture Classification is a fundamental issue in computer vision and image processing, playing a significant role in many applications such as medical image analysis, remote sensing, object recognition, document analysis, environment modeling, content-based image retrieval and many more.
Source: Improving Texture Categorization with Biologically Inspired Filtering
Benchmarks
These leaderboards are used to track progress in Texture Classification
ElBa
Multidimensional Texture Perception
ISOD
CBTex
Most implemented papers
Lacunarity Pooling Layers for Plant Image Classification using Texture Analysis
advanced-vision-and-learning-lab/2024_v4a_lacunarity_pooling_layer
•
•
This work contributes to the evolving landscape of artificial neural network architectures by introducing a novel pooling layer that enriches the representation of spatial features.
