mehdi-abbasi Goto Github PK

antropy

AntroPy: entropy and complexity of (EEG) time-series in Python

bitcoin

Bitcoin Core integration/staging tree

chatpythonsocket

a simple chat code with python socket programming

dcdicl_denoising

Official implementation of Deep Convolutional Dictionary Learning for Image Denoising.

ddlcn

[WACV 2019 Oral] Deep Micro-Dictionary Learning and Coding Network

deep_facial_expression_recognition

dicodile

Experiments for "Distributed Convolutional Dictionary Learning (DiCoDiLe): Pattern Discovery in Large Images and Signals"

dsrc

Tensorflow implementation of "Deep sparse representation-based classification"

git_webinar

gittutorial

groupcdl-tip

Implementation of GroupCDL, CDLNet, and GDLNet image restoration neural networks in Julia.

kair

Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

knn-bayes-rf-from-scratch

Simple implementation of knn & Bayesian Learning & Random Forest from Scratch

lab-description

Applied Control & Robotics Research Laboratory

ldwin

Link Discovery for Windows

matlab_dictionary_learning

matlab implementation of online dictionary learning with example driver code

mehdi-abbasi

Config files for my GitHub profile.

ml_course_researhstudy_prj

mlp-from-scratch

simple implementation of Multi Layer Perceptron(MLP)

modl

Randomized online matrix factorization

online-dictionary-learning-demo

online-dictionary-learning-for-sparse-coding

Implementation of the paper "Online dictionary learning for sparse coding" (Mairal et al).

onlinedictionarylearning

Fast Implementation of Online Dictionary Learning for Sparse Coding Algorithm

python_course

research

Last updated: 2020-01-12. Or, check my Google Scholar for good.

segment-anything-medical-evaluation

Code for "Segment Anything Model for Medical Image Analysis: an Experimental Study"

sparselandtools

:sparkles: A Python package for sparse representations and dictionary learning, including matching pursuit, K-SVD and applications.