Deep Learning, Ian Goodfellow, Yoshua Bengio, and Aaron Courville, 2016 (MIT Press) - Provides a comprehensive theoretical foundation for convolutional networks, including the convolution operation, filter properties, and architectural considerations.
Gradient-Based Learning Applied to Document Recognition, Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner, 1998Proceedings of the IEEE, Vol. 86 (IEEE)DOI: 10.1109/5.726791 - A foundational paper introducing LeNet-5, demonstrating early successful applications of convolutional neural networks for image processing tasks.
Deep Learning with Python, François Chollet, 2021 (Manning Publications) - Offers practical guidance on implementing convolutional layers using Keras, explaining parameters like filters, kernel size, strides, and padding (2nd edition).