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Publication Type : Journal Article
Publisher : International Journal of Scientific Engineering Research
Authors : Dr. Sowmya V., P., S. K., and Deepika, J.
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Verified : Yes
Year : 2014
Abstract : Convolutional Neural Networks (CNNs) have been established as a powerful class of models for image recognition problems. Inspired by a blog post , we tried to predict the probability of an image getting a high number of likes on Instagram. We modified a pre-trained AlexNet ImageNet CNN model using Caffe on a new dataset of Instagram images with hashtag ‘me’ to predict the likability of photos. We achieved a cross validation accuracy of 60% and a test accuracy of 57% using different approaches. Even though this task is difficult because of the inherent noise in the data, we were able to train the model to identify certain characteristics of photos which result in more likes.