pedro rohde's Projects
Image augmentation library in Python for machine learning.
Some important deep learning papers.
The framework to generate a Dockerfile, build, test, and deploy a docker image with OpenVINOβ’ toolkit.
face recognition streamlit app
Financial math calculator app: debt amortization and investment simulation
Research on video compression using the FlowNet
My solutions to deeplearning.ai's GANs specialization programming assignments
Functional Data Analysis: curve alignment through landmark registration.
Digital Audio: Speech and Music, lab sessions - 3rd year Electronics Engineering and Signal Processing at INP-ENSEEIHT
C++ Project: Circuit Simulation - 2nd year Electronics Engineering and Signal Processing at INP-ENSEEIHT
Project based on Deep Image Prior article - 2nd year Electronics Engineering and Signal Processing at INP-ENSEEIHT
Image Processing Project: Defocus Map Estimation - 2nd year Electronics Engineering and Signal Processing at INP-ENSEEIHT
Signal Processing Project: Electrocardiogram Signal Analysis - 2nd year Electronics Engineering and Signal Processing at INP-ENSEEIHT
Geometric Modeling lab sessions - 3rd year Electronics Engineering and Signal Processing at INP-ENSEEIHT
Inverse Problems Project: Deconvolution of a Sparse Signal - 3rd year Electronics Engineering and Signal Processing at INP-ENSEEIHT
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Introductions to key concepts in quantum machine learning, as well as tutorials and implementations from cutting-edge QML research.
My solutions to the Quantum Machine Learning MOOC (University of Toronto/edX)
π€ Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Digital Circuits Final Project: Microwave - 2nd year Electronics Engineering at UFSC [EEL5105 - Circuitos e TΓ©cnicas Digitais]
Numerical Analysis course and project - 2nd year Electronics Engineering at UFSC [EEL7031 - Computação CientΓfica II]
Research on neural network architectures for compressed video quality enhancement.