Semantic Based Answering Technique for Image Query in Mobile Cloud Computing

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P. Calduwel Newton, T. Cynthia


This paper aims an answering technique that identifies the disease name in tomato plants by giving the affected plant�s image as input and enables the users to retrieve the preventive and controlling methods of the disease. Classifying an image accurately, takes different forms in different researches. Content Based Image Retrieval and Google�s reverse image search are few outcomes of such researches. Still, there is a need for a technique that recognizes images like how humans classify based on their experience. This work comes with a better solution by combining image classification in human�s perspective with semantic based answering. TensorFlow is an open source algorithm that is released by Google is an effective tool for classifying images and ontology that gives very accurate answers to the user queries are the technologies that are used in the proposed technique. The images and details of tomato crop diseases are collected from different forums and the glossary terms used in ontology are taken from the web.

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How to Cite
, P. C. N. T. C. (2018). Semantic Based Answering Technique for Image Query in Mobile Cloud Computing. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 4(4), 557–562. Retrieved from