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GlossaryConvolutional Neural Network

deep learning model for analyzing visual data

A Convolutional Neural Network (CNN) is a type of deep learning algorithm specifically designed for processing structured grid data like images. It uses layers of convolutional filters to automatically and adaptively learn spatial hierarchies of features from input data, making it highly effective for tasks such as image recognition, classification, and segmentation.

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research Investigating Different Deep Learning Models for Classification of Folliculitis

May 2023

GoogLeNet is the best model for identifying folliculitis.

research Deep Learning-Based Trichoscopic Image Analysis and Quantitative Model for Predicting Basic and Specific Classification in Male Androgenetic Alopecia

December 2021 in “Acta dermato-venereologica”

A deep learning model accurately predicts male hair loss types using scalp images.

research Generative Adversarial Networks for Anonymous Acneic Face Dataset Generation

April 2024 in “PLoS ONE”

The method creates realistic, anonymous acne face images for research, achieving 97.6% accuracy in classification.

research Trichoscopy of Alopecia Areata: Hair Loss Feature Extraction and Computation Using Grid Line Selection and Eigenvalue

10 citations, September 2020 in “Computational and Mathematical Methods in Medicine”

Researchers developed an algorithm for self-diagnosing scalp conditions with high accuracy using smart device-attached microscopes.

research Methods of Transfer Learning for Multiclass Hair Disease Categorization

December 2023

Transfer learning with three neural network architectures accurately classifies hair diseases.

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