Convolutional neural network for color images classification

Nora Ahmed Mohammed, Mohammed Hamzah Abed, Alaa Taima Albu-Salih

Abstract


Artificial intelligent and application of computer vision are an exciting topic in last few years, and its key for many real time applications like video summarization, image retrieval and image classifications. One of the most trend method in deep learning is a convolutional neural network, used for many applications of image processing and computer vision. In this work convolutional neural networks CNN model proposed for color image classification, the proposed model build using MATLAB tools of deep learning. In addition, the suggested model tested on three different datasets, with different size. The proposed model achieved highest result of accuracy, precision and sensitivity with the largest dataset and it was as following: accuracy is 0.9924, precision is 0.9947 and sensitivity is 0.9931, compare with other models.

Keywords


Classification; CNN; Color images; Deep learning; Features extraction

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DOI: https://doi.org/10.11591/eei.v11i3.3730

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