An Image compression simulator that uses Source Extractor and Monte Carlo methods to examine the post compressive effects different compression algorithms have.

Overview

ImageCompressionSimulation

An Image compression simulator that uses Source Extractor and Monte Carlo methods to examine the post compressive effects of different compression algorithms.

Author's Note

This work done behind this program was to investigate the compression effects of different compression algorithms on an real science image which then has over 10000 simulated copies (due to the lack of real data) of it via Monte Carlo methods. These simulated images are then analyzed by Source Extractor- https://sextractor.readthedocs.io/. to examine the pre and post compressive effects on the image.

To be quite honest, this program will probably be outdated and non-functioning by the time someone gets around ACTUALLY trying to run it... The main purpose is to look at legacy code so that I can implement the simulation feature into my other open source project MagnaPY- www.github.com/parkji30/MagnaPY

Some Cool Results from ICS

Some simulated stars using ICS

another simulated star simulated_star

Analysis showing the compression effects of the HCOMPRESS algorithm. We see that the distribution of the ellipticity value detected by source extractor did not get distorted from our Monte Carlo simulation of over 1000 simulated stars as shown above. We conclude that the HCOMPRESS algorithm can be safely used for sources of this nature in our science data.

analysis

Signal to noise plot showing the limitations of Source Extractor. Essentially Source Extractor cannot detect sources with a FWHM less than 1.5 sigma.

signaltonoise

Owner
James Park
Experimental Astrophysicist involved with the BIT and BLAST-TNG collaboration. Interested in magnetism and dark matter.
James Park
Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.

Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner

NVIDIA Corporation 147 Dec 17, 2022
Boundary-aware Transformers for Skin Lesion Segmentation

Boundary-aware Transformers for Skin Lesion Segmentation Introduction This is an official release of the paper Boundary-aware Transformers for Skin Le

Jiacheng Wang 79 Dec 16, 2022
Weighing Counts: Sequential Crowd Counting by Reinforcement Learning

LibraNet This repository includes the official implementation of LibraNet for crowd counting, presented in our paper: Weighing Counts: Sequential Crow

Hao Lu 18 Nov 05, 2022
cl;asification problem using classification models in supervised learning

wine-quality-predition---classification cl;asification problem using classification models in supervised learning Wine Quality Prediction Analysis - C

Vineeth Reddy Gangula 1 Jan 18, 2022
PyTorch implementation of the paper:A Convolutional Approach to Melody Line Identification in Symbolic Scores.

Symbolic Melody Identification This repository is an unofficial PyTorch implementation of the paper:A Convolutional Approach to Melody Line Identifica

Sophia Y. Chou 3 Feb 21, 2022
Listing arxiv - Personalized list of today's articles from ArXiv

Personalized list of today's articles from ArXiv Print and/or send to your gmail

Lilianne Nakazono 5 Jun 17, 2022
Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF shows significant improvements over baseline fine-tuning without data filtration.

Information Gain Filtration Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF sho

4 Jul 28, 2022
Official implementation of Influence-balanced Loss for Imbalanced Visual Classification in PyTorch.

Official implementation of Influence-balanced Loss for Imbalanced Visual Classification in PyTorch.

Seulki Park 70 Jan 03, 2023
Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"

SelfTask-GNN A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper] In this paper, we first deepe

Wei Jin 85 Oct 13, 2022
This folder contains the implementation of the multi-relational attribute propagation algorithm.

MrAP This folder contains the implementation of the multi-relational attribute propagation algorithm. It requires the package pytorch-scatter. Please

6 Dec 06, 2022
Apache Flink

Apache Flink Apache Flink is an open source stream processing framework with powerful stream- and batch-processing capabilities. Learn more about Flin

The Apache Software Foundation 20.4k Dec 30, 2022
Pixray is an image generation system

Pixray is an image generation system

pixray 883 Jan 07, 2023
UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss

UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss This repository contains the TensorFlow implementation of the paper UnF

Simon Meister 270 Nov 06, 2022
EZ graph is an easy to use AI solution that allows you to make and train your neural networks without a single line of code.

EZ-Graph EZ Graph is a GUI that allows users to make and train neural networks without writing a single line of code. Requirements python 3 pandas num

1 Jul 03, 2022
Neuron Merging: Compensating for Pruned Neurons (NeurIPS 2020)

Neuron Merging: Compensating for Pruned Neurons Pytorch implementation of Neuron Merging: Compensating for Pruned Neurons, accepted at 34th Conference

Woojeong Kim 33 Dec 30, 2022
Code to reproduce the results for Statistically Robust Neural Network Classification, published in UAI 2021

Code to reproduce the results for Statistically Robust Neural Network Classification, published in UAI 2021

1 Jun 02, 2022
PyTorch/GPU re-implementation of the paper Masked Autoencoders Are Scalable Vision Learners

Masked Autoencoders: A PyTorch Implementation This is a PyTorch/GPU re-implementation of the paper Masked Autoencoders Are Scalable Vision Learners: @

Meta Research 4.8k Jan 04, 2023
A flag generation AI created using DeepAIs API

Vex AI or Vexiology AI is an Artifical Intelligence created to generate custom made flag design texts. It uses DeepAIs API. Please be aware that you must include your own DeepAI API key. See instruct

Bernie 10 Apr 06, 2022
Speeding-Up Back-Propagation in DNN: Approximate Outer Product with Memory

Approximate Outer Product Gradient Descent with Memory Code for the numerical experiment of the paper Speeding-Up Back-Propagation in DNN: Approximate

2 Mar 02, 2022
Easily pull telemetry data and create beautiful visualizations for analysis.

This repository is a work in progress. Anything and everything is subject to change. Porpo Table of Contents Porpo Table of Contents General Informati

Ryan Dawes 33 Nov 30, 2022