Indian Journal of Science and Technology
Year: 2019, Volume: 12, Issue: 32, Pages: 1-12
Aurangzeb Magsi*, Javed Ahmed Mahar and Shahid Hussain Danwar
*Author for correspondence
Department of Computer Science, Shah Abdul Latif University, Khairpur, Pakistan;
Numerous biotechnology software applications are developed to provide computational solutions to complex agricultural problems like identification of diseases and monitoring plant growth. Dates are healthy fruit and its contribution in total G.D.P of Pakistan is approximately 4% in which District Khairpur provides approximately 81% production. Approximately 22 types of Dates are produced in different areas of Pakistan. It is observed that national as well as international emptor are unable to correctly identify the type of dates. Objectives: This study aims to presents a framework for recognition of Dates using Deep Learning technique based on color, shape and size feature extraction methods. Methods: We have established fruit images dataset of 500 images for evaluation purpose likewise 360-dataset. Three types of Dates were selected for experiments like Aseel, Karbalain and Kupro. The range of 500date fruit samples were collected out of which 350 used for training dataset and 150 used for testing purpose. Findings: Experiment performed on the selected samples following the proposed framework. For better accuracy, we have used combination of several hidden layers and 100 epochs which gives the best performance result of 97.2% at 4th epoch. A confusion matrix is used to analyze and measure the results accuracy through which we get 89.2% as a True Positive. Application and Improvements: The outcome will be beneficial for the emptor, researchers and also for automated factory classification.
Keywords: Biotechnology Applications, Color Feature Extraction, Confusion Table, Dates
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