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Image Classification Project - Build an Image Classification Model on a Dataset of T-Shirt Images for Binary Classification
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Image classification - Image classification refers to a process in computer vision that can classify an image according to its visual content. Image classification applications include recognizing various objects, such as vehicles, people, moving objects, etc., on the road to enable autonomous driving.
Transfer Learning - The reuse of a pre-trained model on a new problem is known as transfer learning in machine learning. A machine uses the knowledge learned from a prior assignment to increase prediction about a new task in transfer learning.
In this project, we will be dealing with a binary classification dataset. A model is to be built that can correctly classify a t-shirt image into plain or topographic. We will be building transfer learning models like InceptionV3 and Resnet.
We have a dataset of t-shirt images categorized into 2 types, namely plain(solid) and topography (contains text)
The training, testing and validation folders contain two subfolders (plain and topography) each.
To build a transfer learning model that can perform binary classification on the given dataset of images.
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