Covid-19 Test AI (Deep Learning - NNs) Software. Accuracy is the %96.5, loss is the 0.09 :)

Overview

Covid-19 Test AI (Deep Learning - NNs) Software

I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negative. I created the model with great precision. Sometimes I trained twice (piece by piece), sometimes once. I save the output of both in .txt file and share with you. I would be pleased to present this project to open source. I hope it has become a software that can be used in the field of health and artificial intelligence.

I can say that it has the features of a software that can detect Covid-19 in real time. In this way, it can be determined that the covid is positive or negative with the image processing + segmentation rule thanks to artificial intelligence without PCR testing.

Kind regards,

Emirhan BULUT

Artificial Intelligence - Deep Learning Engineer

Data Source: DataSource ###The coding language used:

Python 3.9.6

###Libraries Used:

Tensorflow

Keras

pixellib

OpenCV

PIL

Covid 19 Test - AI Software - Emirhan BULUT

Developer Information:

Name-Surname: Emirhan BULUT

Contact (Email) : [email protected]

LinkedIn : https://www.linkedin.com/in/artificialintelligencebulut/

Kaggle: https://www.kaggle.com/emirhanai

Official Website: https://www.emirhanbulut.com.tr

Owner
Emirhan BULUT
Machine Learning and Deep Learning Engineer - AI Developer *************************** Student of the Harvard University (CS and AI)
Emirhan BULUT
Pytorch implement of 'Unmixing based PAN guided fusion network for hyperspectral imagery'

Pgnet There's a improved version compared with the publication in Tgrs with the modification in the deduction of the PDIN block: https://arxiv.org/abs

5 Jul 01, 2022
Age Progression/Regression by Conditional Adversarial Autoencoder

Age Progression/Regression by Conditional Adversarial Autoencoder (CAAE) TensorFlow implementation of the algorithm in the paper Age Progression/Regre

Zhifei Zhang 603 Dec 22, 2022
Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge

Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge This is an implementation of the paper,

Mutian He 19 Oct 14, 2022
MDETR: Modulated Detection for End-to-End Multi-Modal Understanding

MDETR: Modulated Detection for End-to-End Multi-Modal Understanding Website • Colab • Paper This repository contains code and links to pre-trained mod

Aishwarya Kamath 770 Dec 28, 2022
[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis

Focal Frequency Loss - Official PyTorch Implementation This repository provides the official PyTorch implementation for the following paper: Focal Fre

Liming Jiang 460 Jan 04, 2023
[ICCV '21] In this repository you find the code to our paper Keypoint Communities

Keypoint Communities In this repository you will find the code to our ICCV '21 paper: Keypoint Communities Duncan Zauss, Sven Kreiss, Alexandre Alahi,

Duncan Zauss 262 Dec 13, 2022
PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"

CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration (NeurIPS 2021) PyTorch implementation of the paper: CoFiNet: Reli

76 Jan 03, 2023
A High-Performance Distributed Library for Large-Scale Bundle Adjustment

MegBA: A High-Performance and Distributed Library for Large-Scale Bundle Adjustment This repo contains an official implementation of MegBA. MegBA is a

旷视研究院 3D 组 336 Dec 27, 2022
This is the repo for Uncertainty Quantification 360 Toolkit.

UQ360 The Uncertainty Quantification 360 (UQ360) toolkit is an open-source Python package that provides a diverse set of algorithms to quantify uncert

International Business Machines 207 Dec 30, 2022
Using Streamlit to host a multi-page tool with model specs and classification metrics, while also accepting user input values for prediction.

Predicitng_viability Using Streamlit to host a multi-page tool with model specs and classification metrics, while also accepting user input values for

Gopalika Sharma 1 Nov 08, 2021
An implementation for the ICCV 2021 paper Deep Permutation Equivariant Structure from Motion.

Deep Permutation Equivariant Structure from Motion Paper | Poster This repository contains an implementation for the ICCV 2021 paper Deep Permutation

72 Dec 27, 2022
Convolutional Neural Network for 3D meshes in PyTorch

MeshCNN in PyTorch SIGGRAPH 2019 [Paper] [Project Page] MeshCNN is a general-purpose deep neural network for 3D triangular meshes, which can be used f

Rana Hanocka 1.4k Jan 04, 2023
PyTorch implementation of UNet++ (Nested U-Net).

PyTorch implementation of UNet++ (Nested U-Net) This repository contains code for a image segmentation model based on UNet++: A Nested U-Net Architect

4ui_iurz1 642 Jan 04, 2023
Rainbow DQN implementation that outperforms the paper's results on 40% of games using 20x less data 🌈

Rainbow 🌈 An implementation of Rainbow DQN which outperforms the paper's (Hessel et al. 2017) results on 40% of tested games while using 20x less dat

Dominik Schmidt 31 Dec 21, 2022
[BMVC'21] Official PyTorch Implementation of Grounded Situation Recognition with Transformers

Grounded Situation Recognition with Transformers Paper | Model Checkpoint This is the official PyTorch implementation of Grounded Situation Recognitio

Junhyeong Cho 18 Jul 19, 2022
DirectVoxGO reconstructs a scene representation from a set of calibrated images capturing the scene.

DirectVoxGO reconstructs a scene representation from a set of calibrated images capturing the scene. We achieve NeRF-comparable novel-view synthesis quality with super-fast convergence.

sunset 709 Dec 31, 2022
Official code for our ICCV paper: "From Continuity to Editability: Inverting GANs with Consecutive Images"

GANInversion_with_ConsecutiveImgs Official code for our ICCV paper: "From Continuity to Editability: Inverting GANs with Consecutive Images" https://a

QingyangXu 38 Dec 07, 2022
FID calculation with proper image resizing and quantization steps

clean-fid: Fixing Inconsistencies in FID Project | Paper The FID calculation involves many steps that can produce inconsistencies in the final metric.

Gaurav Parmar 606 Jan 06, 2023
This repository is for the preprint "A generative nonparametric Bayesian model for whole genomes"

BEAR Overview This repository contains code associated with the preprint A generative nonparametric Bayesian model for whole genomes (2021), which pro

Debora Marks Lab 10 Sep 18, 2022
Object tracking using YOLO and a tracker(KCF, MOSSE, CSRT) in openCV

Object tracking using YOLO and a tracker(KCF, MOSSE, CSRT) in openCV File YOLOv3 weight can be downloaded

Ngoc Quyen Ngo 2 Mar 27, 2022