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3d-mri-brain-tumor-segmentation-using-autoencoder-regularization

Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).

3d_sits_clustering

3D_SITS_Clustering

adaptive-kalman-filter

Perform optimal state estimation for linear systems with adaptive online noise covariance estimation

adaptive-median

Adaptive-median image filter in pure python - use with

adaptive-signal-processing-and-machine-intelligence

Spectrum estimation, adaptive filter, and machine intelligence.

anuga_core

AnuGA for the simulation of the shallow water equation

arsthreshold

This code refers to the first Antecedent Rainfall - Susceptibility threshold model of Monsieurs et al. 2019

automate-gmtsar

Python libraries and modified GMTSAR scripts for running GMTSAR on HPC systems.

autorift

A Python module of a fast and intelligent algorithm for finding the pixel displacement between two images

cartopy-colab

cartopy-tutorial

cartopy_asean_proj

Python code using Cartopy package for plotting maps of ASEAN countries

change-detection-in-remote-sensing-images

change_detection_in_sar_images

Implemented and refined a novel neural network architecture used for abnormal change detection. Successfully predicted the timely change of satellite images by inserting the unsupervised and jointly learned change information of nearby image crops.

chiba_himawari_8

This script can be used for downloading and exporting to NetCDF4. time dimension in this data is every 10 minute. Automatic download and convert with realtime system date can be implemented by using bash (see my next post auto_himawari_8).

chula_insar

InSAR processing chain tools for SBAS interferogram stacking

clawpack

Package for solving hyperbolic systems of partial differential equations

cloudy_flood_prediction

Python and Google Earth Engine ML workflow for estimating inundation beneath clouds for flood mapping based on auxiliary data.

computer_vision_lecture_notebooks

Contains the jupyter notebooks for the practical part of the Computer Vision lecture I held at the University of Applied Sciences Technikum Wien from 2019 to 2022. The topics covered include general image handling and processing, traditional feature engineering, neural networks and deep learning, convolutional neural networks and autoencoders with a focus on segmentation tasks

computervision_moai

Computer vision project (Master of Artificial Intelligence at KU Leuven). Comparison of PCA and autoencoder, classification of images and segmentation on the dataset PASCAL VOC-2009. This project was done in colaboration with Abel Rodríguez (abelrguezr).

convpde

Convolutional Solvers for Partial Differential Equations

crack_detection

VGG + Autoencoders + YOLO_v4 + Detectronn2 (Instance Segmentation)

dagmm

My attempt at reproducing the paper Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection

deciphering_debris-flow_seismograms

dem_connectedcomponents

Connected Components (CC) from longitudinal river profiles for debris flow mapping

dfpenet

A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides

discovery-asf_search

downloadaux_poeorb

Download precision orbit files for sentinel-1 data

earthquake-impact-utils

Utilities to support USGS earthquake shaking and impacts software, such as ShakeMap, PAGER, and groundfailure.

ec21_zheng_etal

An open-source, interactive, and highly customizable workflow for glacier velocity mapping using feature tracking technique and satellite images.