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FRUIT CLASSIFICATION USING ERAS WITH TENSOR FLOW AND DEPLOYMENT IN WEB APPLICATION. Submitted in partial fulfillment of the requirements for the award of Master in Engineering in Department of Computer
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What is how-to-perform-fruit-classification-with-deep-learning-in?
It refers to the process of using deep learning techniques to classify different types of fruits based on their features, such as color, texture, and shape using neural networks.
Who is required to file how-to-perform-fruit-classification-with-deep-learning-in?
Typically, researchers, data scientists, and developers working on projects involving deep learning and image classification in agricultural technology or machine learning applications are required to file this.
How to fill out how-to-perform-fruit-classification-with-deep-learning-in?
To fill it out, you need to gather datasets of images for different fruits, preprocess these images, choose a deep learning model, and train the model using labeled data, followed by testing and validating its accuracy.
What is the purpose of how-to-perform-fruit-classification-with-deep-learning-in?
The purpose is to create an efficient system that can automatically classify fruits from images, which can be useful in various applications such as agriculture, food quality control, and inventory management.
What information must be reported on how-to-perform-fruit-classification-with-deep-learning-in?
Information such as the dataset description, model architecture used, training and testing results, accuracy metrics, and the implementation details must be reported.
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