Covers Convolutional Neural Networks, including layers, training strategies, standard architectures, tasks like semantic segmentation, and deep learning tricks.
Introduces fundamental notions in digital filtering, covering 2D filtering approaches, linear filters, stability, FIR and IIR filters, frequency domain filtering, and Gaussian filters.
