Dataset used to train a Convolutional Neural Network dedicated to skin pore detection and classification
Authors/Creators
- 1. PhD Information-Technology-FB&L, University MB, Teodora Drajzera 27, Belgrade, Serbia
Description
This data note pertains to the dataset used during the training of a neural network dedicated to the classification of facial skin based on pore condition. The dataset comprises a total of 3086 images categorized into 5 folders, thereby defining a total of 5 classes for facial skin categorization. The folders are labeled as numbers: 1, 2, 3, 4, and 5, corresponding to the categories of facial skin: very good, good, normal, poor, very poor. All images are in "jpg" format with a resolution of 224x224 pixels. On the this way prepared dataset, without any additional processing, is accepted as input by functions from the Keras library within the TensorFlow development environment.
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The data that support the findings of this study are available from the corresponding author Čedomir Vasić, upon reasonable request. There is a justifiable concern that the data could be used to develop commercial software that potentially threatens the market position of the institution that facilitated the dataset's creation. If the author concludes that the data will be exclusively used for scientific research purposes, access to the data will be granted to interested researchers with pleasure.
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