Image Processing I: Quantization and Histogram Analysis

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Explores analog-to-digital conversion, neural signal optimization, multichannel architectures, and on-chip compression techniques in neuroengineering.

Quantization: Basics and Uniform Input

Explores quantization in digital devices, covering scalar and uniform quantization, mean square error, and signal-to-noise ratio.

Model Compression: Techniques for Efficient NLP Models

Explores model compression techniques in NLP, discussing pruning, quantization, weight factorization, knowledge distillation, and attention mechanisms.

Model Compression Techniques: Enhancing Neural Networks

Covers model compression techniques to enhance the efficiency of large language models in production settings.

Fundamental Notions - I

Explores fundamental notions in image and video processing, covering applications and key concepts like color quantization and 2D Fourier Transform properties.

Quantization: Topological Operators

Covers the quantization of topological operators and Ising models on square lattices.

Quantum Optics I: Quantized Harmonic Oscillator

Covers the quantization of the harmonic oscillator and its implications on the electromagnetic field, including vacuum energy effects.

Smart Sensors for the IoT: ADCs Fundamentals

Explores ADCs fundamentals for IoT smart sensors, covering quantization, non-idealities, and topologies.

Jarzynski Equation and Quantum Circuits

Explores the Jarzynski equation and the quantization of electrical circuits in quantum harmonic oscillators.

JPEG 2000: Image Compression

Explores image compression principles, focusing on JPEG 2000, covering transform-based coding, quantization, entropy coding, region of interest, error resilience, and software implementations.