mohamed-gamal-khattab Goto Github PK

advanced-feature-selection-toolbox

This toolbox offers advanced feature selection tools. Several modifications, variants, enhancements, or improvements of algorithms such as GWO, FPA, SCA, PSO and SSA are provided.

background_removal

removal of background from image.

brain-mr-image-preprocessing

Preprocess Brain MR Images

brain_tumor_classification

Implementation and performance analysis of the use of a stacking ensemble machine learning algorithm and image features extraction with a brain tumor classification problem

cervical-cancer-cnn-ga

Deep feature selection using GA for classification of cervical cytology images.

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

feature-engineering-and-feature-selection

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

metaheuristics-toolbox

A Collection Of The State-of-the-art Metaheuristic Algorithms In Python (Metaheuristic/Optimizer/Nature-inspired/Biology)

ms-challenge-2016

Multiple Sclerosis Lesion Segmentation

ms-detect

Multiple sclerosis detection from MRI images.

multiple-sclerosis-detection

nn-svg

Publication-ready NN-architecture schematics.

study-of-detection-brain-tumor-with-machine-learning

Tumor is an uncontrolled growth of tissues in any part of the body. Tumors are of different types and hence they have different treatments. Detection of tumor in the earlier stages makes the treatment possible. Here we review different segmentation methods associated with feature extraction from Magnetic Resonance Imaging (MRI) of brain. We also discuss different machine learning and classification algorithms that use to classify normal and cancerous tissues. Finally, we propose an automatic tumor detection system

traditional-feature-extraction

Feature Extraction is an integral step for Image Processing jobs. This repository contains the python codes for Traditional Feature Extraction Methods from an image dataset, namely Gabor, Haralick, Tamura, GLCM and GLRLM.

u2net_bgremove_code

Jupyter Notebook containing code for Image & Video background removal using u2net

wrapper-feature-selection-toolbox-python

This toolbox offers 13 wrapper feature selection methods (PSO, GA, GWO, HHO, BA, WOA, and etc.) with examples. It is simple and easy to implement.

zernike

Python code for Zernike polynomials