Name: Marcus Chaffim
Type: User
Company: University of Brasília
Bio: Marcus Chaffim is Assistant Professor of Electronic Engineering and member of the Graduate Program in Biomedical Engineering at University of Brasília, Brasil.
Twitter: chaffim
Location: https://goo.gl/x2TYo0
Blog: https://orcid.org/0000-0001-5876-9910
Marcus Chaffim's Projects
IoT friendly arithmetic compression and encryption
Exercises for the book Artificial Intelligence: A Modern Approach
Java implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
Julia implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
Algoritmos e Programação de Computadores
Code for ANTS book (Cohen, 2012, MIT Press)
Full HRV analysis of Arduino pulse sensor, using Python signal processing and time series techniques. Chaotic, Fourier, Wavelet, Regression, Neural Net.
Arithmetic Coding for Data Compression
ArrayFire: a general purpose GPU library.
Testing various methods for choosing tANS entropy coding automata
PoC for AIS broadcast authentication based on TESLA
This repo has samples for dev kits using the Azure IoT middleware for FreeRTOS
Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
Fast and Strong Burrows Wheeler Model
Blender Addon to render light fields with depth and disparity maps
Machine Leaning Approaches for Classification of Children with Autism Spectrum Disorder
Modeling the spread of COVID-19
Codificação e Compressão de Sinais, Imagens e Vídeo
A Python-embedded modeling language for convex optimization problems.
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
Matlab files with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz http://www.databookuw.com/
IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by J. Nathan Kutz and Steven L. Brunton
DDSP: Differentiable Digital Signal Processing
Image restoration with neural networks but without learning.
Neural Reconstruction for Foveated Rendering and Video Compression using Learned Statistics of Natural Videos
Python port of the Dual-Tree Complex Wavelet Transform toolbox for MATLAB
Toolkit to compute metric scores, create figures, and validate submissions