%0 Journal Article %1 noauthororeditor %A Chandak, Shivani Machha | Nikita Jadhav | Himali Kasar | Prof. Sumita %D 2020 %J International Journal of Trend in Scientific Research and Development %K (CNN) Classification Convolutional Information Leaf Mobile Net Neural Technology diseases network %N 2 %P 1056-1058 %T Crop Leaf Disease Diagnosis using Convolutional Neural Network %U https://www.ijtsrd.com/engineering/information-technology/29952/crop-leaf-disease-diagnosis-using-convolutional-neural-network/shivani-machha %V 4 %X The major problem that the farmers around the world face is losses, because of pests, disease or a nutrient deficiency. They depend upon the information that they get from the agricultural departments for the diagnosis of plant leaf disease. This process is lengthy and complicated. Here comes a system to help farmers everywhere in the world by automatically detecting plant leaf diseases accurately and within no time. The proposed system is capable of identifying the disease of majorly 5 crops which are corn, sugarcane, wheat, and grape. In this paper, the proposed system uses the Mobile Net model, a type of CNN for classification of leaf disease. Several experiments are performed on the dataset to get the accurate output. This system ensures to give more accurate results than the previous systems. Shivani Machha | Nikita Jadhav | Himali Kasar | Prof. Sumita Chandak ""Crop Leaf Disease Diagnosis using Convolutional Neural Network"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020, URL: https://www.ijtsrd.com/papers/ijtsrd29952.pdf Paper Url : https://www.ijtsrd.com/engineering/information-technology/29952/crop-leaf-disease-diagnosis-using-convolutional-neural-network/shivani-machha

@article{noauthororeditor, abstract = {The major problem that the farmers around the world face is losses, because of pests, disease or a nutrient deficiency. They depend upon the information that they get from the agricultural departments for the diagnosis of plant leaf disease. This process is lengthy and complicated. Here comes a system to help farmers everywhere in the world by automatically detecting plant leaf diseases accurately and within no time. The proposed system is capable of identifying the disease of majorly 5 crops which are corn, sugarcane, wheat, and grape. In this paper, the proposed system uses the Mobile Net model, a type of CNN for classification of leaf disease. Several experiments are performed on the dataset to get the accurate output. This system ensures to give more accurate results than the previous systems. Shivani Machha | Nikita Jadhav | Himali Kasar | Prof. Sumita Chandak ""Crop Leaf Disease Diagnosis using Convolutional Neural Network"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020, URL: https://www.ijtsrd.com/papers/ijtsrd29952.pdf Paper Url : https://www.ijtsrd.com/engineering/information-technology/29952/crop-leaf-disease-diagnosis-using-convolutional-neural-network/shivani-machha }, added-at = {2020-05-14T10:48:59.000+0200}, author = {Chandak, Shivani Machha | Nikita Jadhav | Himali Kasar | Prof. Sumita}, biburl = {https://www.bibsonomy.org/bibtex/2d79bb24f951f870d5626a32f75fe0e17/ijtsrd}, interhash = {04ebf4fa1eaff0a01b6e9d0fc9fe8360}, intrahash = {d79bb24f951f870d5626a32f75fe0e17}, issn = {2456-6470}, journal = {International Journal of Trend in Scientific Research and Development}, keywords = {(CNN) Classification Convolutional Information Leaf Mobile Net Neural Technology diseases network}, language = {English}, month = feb, number = 2, pages = {1056-1058}, timestamp = {2020-05-14T10:48:59.000+0200}, title = {Crop Leaf Disease Diagnosis using Convolutional Neural Network }, url = {https://www.ijtsrd.com/engineering/information-technology/29952/crop-leaf-disease-diagnosis-using-convolutional-neural-network/shivani-machha}, volume = 4, year = 2020 }