bhavul/Caltech-101-Object-Classification
Multiple approaches tried for Object classification on Caltech 101 Dataset
This project helps computer vision researchers and students understand and perform image classification. It takes images from the Caltech 101 dataset and outputs predicted object categories, allowing users to experiment with different neural network models for identifying objects like airplanes or watches. The primary users are those learning or experimenting with deep learning for object recognition.
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Use this if you are a student or researcher wanting to learn about or experiment with deep learning models for image classification on a well-known dataset.
Not ideal if you need to classify objects outside the 101 categories of the Caltech 101 dataset, or if you're looking for a production-ready object detection solution rather than a classification experiment.
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Oct 21, 2020
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