IDENTIFICATION AND PESTICIDE SUGGESTION OF DISEASES IN RICE PLANT (Oryza sativa) USING IMAGE PROCESSING & DEEP LEARNING ALGORITHM (International Journal of Engineering Sciences & Management Research, 2018)
Rice is the staple food of about 135 million people of Bangladesh. Several diseases such as leaf blast, neck blast, leaf scald etc. of rice and rice plant leafs are major constraints and matter of concerns for the production of rice. Therefore, it is an advantageous to investigate the potential outcomes of abusing Information Technology based methods and practices to create rice development in the nation. Primary target of this thesis is to build up an application to analyze rice diseases through their visual side effects so appropriate diseases control techniques can be adjusted keeping in mind the end goal to procure a decent collect in rice plantation. This thesis paper develops the way toward recognizing rice plant diseases through visual symptoms of the contaminated region of a plant. The system applies images processing techniques to group unhealthy rice plant leaves and distinguish the infection. The system distinguishes the name of the diseases and suggests the appropriate solution for control it.