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Behavior Analysis of Visualization Images Using Deep Learning Approach

The proliferation of unstructured data is overwhelming in business space, converging through texts, images, videos & media generated via PDFs, emails, social sites and various other forums. While the amount of data being generated is increasing at rapid scale, it provides a great challenge to various business units to summarize, analyze and understand the data and to make better business decisions. This paper proposes a neural network model which classifies the images of different charts and bar-graph types namely 2D, 3D, stepped, interpolated, multi-axis etc to gain an insight for the enhancement of customer intelligence as well as performing various calculations on behalf of company's perspective to develop generic plug and play adaptation logic. Classification of image (notably jpeg and png) is conducted using Convolution Neural Network which is a supervised deep learning model which is developed based on the inspiration of connected neurons of visual cortex of animals performs training on images and extracts the features to classify the image class and the bounding box logic is used to specify the focal points of transition.