YOUTUBE LINK :- https://youtu.be/T8ioE7U_WgM
PPT LINK :- https://docs.google.com/presentation/d/1Y0LPr-e5AmsAOl7l8H5N1QEmXRlubCC8aYS2_Abefg4/edit?usp=sharing
Approx. 9 percent of the global population is suffering from hunger and there is the issue of quality of food, and the main challenge is to get the right food to the right places with minimal time and cost. As Much of the world’s food is grown by small-scale, independent farms and these farms suffer from the problem like crop disease.
If we can tackled this problem at initial stage then there is possibility of producing healthy crop. This can be achieved by using machine learning and deep learning based model, and then inspecting whether the crop is healthy or not (disease free),and if it is contaminated so getting right suggestion and advice for its treatment. This approach can be efficacious as we will be able to predict the cause at initial stage and then we can deliver healthy food.
It is a set of cloud computing services for business offered by the information technology company IBM. It combines platform as a service (PaaS) with infrastructure as a service (IaaS).It offers the most open and secure public cloud for business, a next-generation hybrid multi cloud platform, advanced data and AI capabilities, and deep enterprise expertise.
services offered by ibm cloud- Compute,Containers,AI,Storage,Database,Network and security.
Watson Machine Learning is a service on IBM Cloud with features for training and deploying machine learning models and neural networks. Watson Machine Learning enables you to build, train, deploy, and manage machine learning and deep learning models. Watson Machine Learning supports popular frameworks, including: TensorFlow, Caffe, PyTorch, and Keras to build and deploy models. Dynamically retrain models with continuous learning. Bring any projects into production, including open source, third-party and IBM tools.
It is a Python-based free and open-source web framework that follows the model–template–views (MTV) architectural pattern. Django's primary goal is to ease the creation of complex, database-driven websites. The framework emphasizes reusability and "pluggability" of components, less code, low coupling, rapid development, and the principle of don't repeat yourself.
Training set A training dataset is a dataset of examples used during the learning process and is used to fit the parameters of a classifier.
A validation dataset is a dataset of examples used to tune the hyperparameters of a classifier.
Training accuracy of a model is 0.9696. Validation accuracy of a model is 0.9633.
As we know 85% crop disease are caused by fungus,bacteria , virus etc. and this is one of the main cause for the unavailability of healthy food or hunger. As we know that technology plays a great role in this era, so we had technologies which can be a solution to our problem , Deep Convolutional Neural Networks(DCNN) has been successfully applied in various fields, we had also tried to eradicate the problem with the usage of this technology. This technology has freshly moved in the domain of Just-In-Time crop disease detection and our aim is to develop an AI based crop disease detector using DCNN . Through this farmers will be able to detect the problem at earlier stages and will get proper solution and suggestion. In this way we will be able to produce healthy crop and can serve our people with healthy food , a step towards eradicating hunger.
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