anasBahou
Trying to be as free as possible. However, I am working on self-discipline for long term goals
MyselfFrance
Pinned Repositories
ai-project-template
A logical, reasonably standardized, but flexible project template for creating new AI based projects along with Flask APIs by using cookiecutter.
Ancient-Language-Decipherer
Creating a model for the recognition and classification of ancient Egyptian Hieroglyphs. Using transfer learning on convolutional neural networks created with TensorFlow 2.0
ARFlow
The official PyTorch implementation of the paper "Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow Estimation".
articles
A repository for the source code, notebooks, data, files, and other assets used in the data science and machine learning articles on LearnDataSci
awesome-colab-notebooks
Collection of google colaboratory notebooks for fast and easy experiments
awesome-cto
A curated and opinionated list of resources for Chief Technology Officers, with the emphasis on startups
cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
CUDA_ImageConvolution
Implementations of 2D Image Convolution algorithm with CUDA (using global memory, shared memory and constant memory)
cuSpeckle
PoreFlow-Net
3D CNN to predict single-phase flow velocity fields
anasBahou's Repositories
anasBahou/ai-project-template
A logical, reasonably standardized, but flexible project template for creating new AI based projects along with Flask APIs by using cookiecutter.
anasBahou/Ancient-Language-Decipherer
Creating a model for the recognition and classification of ancient Egyptian Hieroglyphs. Using transfer learning on convolutional neural networks created with TensorFlow 2.0
anasBahou/awesome-colab-notebooks
Collection of google colaboratory notebooks for fast and easy experiments
anasBahou/awesome-cto
A curated and opinionated list of resources for Chief Technology Officers, with the emphasis on startups
anasBahou/cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
anasBahou/cuSpeckle
anasBahou/cuSpeckle_lab
anasBahou/deepo
Set up deep learning environment in a single command line.
anasBahou/FastFlowNet
FastFlowNet: A Lightweight Network for Fast Optical Flow Estimation (ICRA 2021)
anasBahou/first_jp_book
test jupyter book
anasBahou/flownet2-pytorch
Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
anasBahou/GPUCorrel
anasBahou/LiteFlowNet
LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation, CVPR 2018 (Spotlight paper, 6.6%)
anasBahou/ml-design-patterns
Source code accompanying O'Reilly book: Machine Learning Design Patterns
anasBahou/muDIC
Digital Image Correlation in Python
anasBahou/MultiDIC
Matlab 3D Digital Image Correlation Toolbox
anasBahou/PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
anasBahou/pytorch-liteflownet3
anasBahou/pytorch-spynet
a reimplementation of Optical Flow Estimation using a Spatial Pyramid Network in PyTorch
anasBahou/pytorchTutorial
PyTorch Tutorials
anasBahou/qmc
A Quasi-Monte-Carlo Integrator Library with CUDA Support
anasBahou/RAFT
anasBahou/rpi-camera
Raspberry Pi High Speed Camera
anasBahou/SelFlow
SelFlow: Self-Supervised Learning of Optical Flow
anasBahou/StrainNet
Subpixel displacement and strain fields estimation with deep learning
anasBahou/tensorboard-aggregator
Aggregate multiple tensorboard runs to new summary or csv files
anasBahou/test_jp_book
my first jupyter book
anasBahou/TimeSeriesForecasting-DeepLearning
An experiemtal review on deep learning architectures for time series forecasting
anasBahou/vegasflow
VegasFlow: accelerating Monte Carlo simulation across multiple hardware platforms
anasBahou/Video-Compression-Net
A new approach to video compression by refining the shortcomings of conventional approach and substituting each traditional component with their neural network counterpart. Our proposed work consists of motion estimation, compression and compensation and residue compression, learned end-to-end to minimize the rate-distortion trade off. The whole model is jointly optimized using a single loss function. Our work is based on a standard method to exploit the spatio-temporal redundancy in video frames to reduce the bit rate along with the minimization of distortions in decoded frames. We implement a neural network version of conventional video compression approach and encode the redundant frames with lower number of bit.