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Introduces convolutional neural networks for image processing, covering basic components, architectures, and practical applications, including denoising and segmentation.
Explores the evolution of CNNs in image processing, covering classical and deep neural networks, training algorithms, backpropagation, non-linear steps, loss functions, and software frameworks.
Explores non conceptual knowledge systems through image translation, video synthesis, self-supervised learning challenges, and universal representations.
Delves into the 'digital turn' in history, examining historical research using digitized newspapers and exploring text reuse, word embeddings, and data visualization.
