Potato Plant Disease Classification and Detection Using Deeplearning and Python 2022-23| 100% code

With the enhancement in agricultural technology and the use of artificial intelligence in diagnosing plant diseases, it becomes important to make pertinent research to sustainable agricultural development. Various diseases like early blight and late blight immensely influence the quality and quantity of the potatoes and manual interpretation of these leaf diseases is quite time-taking and cumbersome. As it requires tremendously a good level of expertise, efficient and automated detection of these diseases in the budding phase can assist in ameliorating the potato crop production. Previously, various models have been proposed to detect several plant diseases. In this video a model is presented that uses pre-trained models like RESNET50 for fine-tuning(transfer learning) to extract the relevant features from the dataset. our model gave 100% training accuracy and 98.5% validation accuracy.potato disease detection using deeplearning is done using python to very good accuracy.

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