Abstract
Starting from images captured on mobile phones, advertisements popping up on our internet browser to e-retail sites displaying flashy dresses for sale, every day we are dealing with a large quantity of visual information and sometimes, finding a particular image or visual content might become a very tedious task to deal with. By classifying the images into different logical categories, our quest to find an appropriate image becomes much easier. Image classification is generally done with the help of computer vision, eye tracking and ways as such. What we intend to implement in classifying images is the use of deep learning for classifying images into pleasant and unpleasant categories. We proposed the use of deep learning in image classification because deep learning can give us a deeper understanding as to how a subject reacts to a certain visual stimuli when exposed to it.
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Tamuly, S., Jyotsna, C., Amudha, J. (2020). Deep Learning Model for Image Classification. In: Smys, S., Tavares, J., Balas, V., Iliyasu, A. (eds) Computational Vision and Bio-Inspired Computing. ICCVBIC 2019. Advances in Intelligent Systems and Computing, vol 1108. Springer, Cham. https://doi.org/10.1007/978-3-030-37218-7_36
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DOI: https://doi.org/10.1007/978-3-030-37218-7_36
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