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@article{151796,
        author = {Sneha Paherwar and Shrishti Paherwar and Sakshi Mishra and Aman Patil and Saurav Anasane and Mirza Moiz Baig},
        title = {Agricultural Drone for Monitoring and Crop Disease Detection},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {1081-1085},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151796},
        abstract = {This paper propose a new approach of technology in agricultural field i.e. agricultural drone which works on monitoring the plant healthiness. The main approach of the research is to analyze the healthiness of plant and to detect the different diseases by applying neural network tool, image pre-processing method based on color changes, texture pattern, gradient, shape changes. After recognizing the disease, it will provide a medicament for it and analyze the defected region of the plant. This will be beneficial for farmer, which will ultimately meet the robust demand of today’s generation. Apart from this, there is an additional features of leaf classification. Some of the factors that can affect the whole field plants are some growth of unwanted plants, the growth of this plant can’t be recognized initially but after classifying the leaves in the field majority of the leaves will be of same pattern but the different kind of leaves will be considered as unwanted plants by providing a dataset to the neural network.},
        keywords = {CNN, Image Processing, Clustering},
        month = {},
        }