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: The extracted feature vector can be high-dimensional. Techniques like PCA (Principal Component Analysis) can be used to reduce its dimensionality while retaining most of the information. Assuming the keyword is related to a search

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: The first step involves preprocessing the image. This includes resizing it to a compatible size for the deep learning model, normalizing the pixel values, and possibly applying data augmentation techniques.