Covers convolutional neural networks, filter operations, and their applications in signal processing and image analysis.
Explores fundamental notions in image and video processing, covering applications and key concepts like color quantization and 2D Fourier Transform properties.
Covers the basics of image processing and its applications in various fields.
Covers the sampling theorem, impulse train sampling, bandlimited signals, and the Nyquist rate.
Explores signals, instruments, and systems, covering ADC, Fourier Transform, sampling, signal reconstruction, aliasing, and anti-alias filters.
Explores nuclear magnetic resonance, MRI principles, pulse sequences, image reconstruction, safety considerations, and volume normalization in brain imaging.
