Deep Learning algorithms such as Convolutional Neural Networks (CNN/ConvNet) use a dataset to assign weights and biases to various aspects/objects in the image, and then differentiate between them based on those weights and biases. As compared to other classification algorithms, ConvNet requires much less pre-processing. With sufficient training, ConvNets can learn the filters/characteristics used in primitive methods.

IMAGE RECOGNITION USING CONVOLUTIONAL NEURAL NETWORK

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