Deep learning
Deep learning has a big impact on computer vision and image recognition, and achieves a higher level of accuracy than other machine learning and artificially intelligent algorithms. Deep learning is not a new concept; it was introduced to the community around 1986, but it started a revolution around 2012 when new GPU hardware was optimized for parallel computing and Convolutional Neural Network (CNN) implementations and other techniques allowed the training of complex neural network architectures in reasonable times.
Deep learning can be applied to multiple use cases such as image recognition, object detection, voice recognition, and natural language processing. Since version 3.4, OpenCV has been implementing deep learning algorithms—in the latest version, multiple importers for important frameworks such as TensorFlow and Caffe have been added.
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