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@article{151694,
        author = {Nidhi Nagdeve and Rutuja Pande and Sakshi Gajwani and Archana. K},
        title = {Monitoring Plant Infections using Soft Computing and Image processing Techniques},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {541-546},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151694},
        abstract = {Agriculture plays an important role in farmer’s life. Sometimes manual identification of disease is time consuming and need of labor is more. One of the most important facts that reduce the growth of plants is disease attack. Overall study about agriculture shows that quality and quantity of agricultural products may be reduced due to various factors of plant diseases. These diseases can be more easily identified by using machine learning approach as compared to manual method. Hence machine learning method can be used to identify the affected leaf images. Images captured by camera will be processed using different image processing technique. These techniques will help in identifying plant diseases thereby increasing the yield of plants. This survey paper describes plant disease identification using Machine Learning Approach and study in detail about various techniques for disease identification and classification is also done.},
        keywords = {Crop disease recognition. Crop disease monitoring system. Internet of things (IoT). Sum and difference histogram (SADH)},
        month = {},
        }