Topic: malaria-detection Goto Github
Some thing interesting about malaria-detection
Some thing interesting about malaria-detection
malaria-detection,The project includes OpenVINO optimized image classification fast.ai model used to learn and classify healthy and infected blood smear malaria images.
User: alihussainia
malaria-detection,This app utilizes machine learning model to identify parasitized malaria cell and uninfected cells
User: anindra123
malaria-detection,The projects I do in Machine Learning with PyTorch, keras, Tensorflow, scikit learn and Python.
User: anubhavshrimal
malaria-detection,Compare Naive Bayes, SVM, XGBoost, Bagging, AdaBoost, K-Nearest Neighbors, Random Forests for classification of Malaria Cells
User: anubhavshrimal
malaria-detection,This repository contains code for a malaria detection system using a pre-trained ResNet50 model on TensorFlow. The model is trained to detect malaria parasites in cell images.
User: arham-kk
malaria-detection,Malaria Detection Project on Malaria Cells
User: arijitiiest
malaria-detection,A generalized deep learning-based framework for assistance to the human malaria diagnosis from microscopic images
User: benhabiles-projects
malaria-detection,This project comprises predicting different types of disease at one place Pneumonia, Malaria, Liver Disease and Cardiovascular Disease
Organization: data-science-community-srm
malaria-detection,Convolutionnal Neural Network reaches 94% test accuracy on Malaria cell dataset (https://www.kaggle.com/iarunava/cell-images-for-detecting-malaria)
User: ell-hol
malaria-detection,
User: erickdiaz
malaria-detection,The objective of this project is to use data collected by the National Institute of health to train a convolutional neural network to predict whether a blood cell is Uninfected or Parasitized by Malaria.
User: fetterollie
malaria-detection,Malaria is a serious global health problem that affects millions of people each year. One of the challenges in diagnosing malaria is identifying infected cells from microscopic images of blood smears. Convolutional Neural Networks (CNNs) are a type of deep learning algorithm that have been used for image classification tasks etc
User: gokul-001
malaria-detection,All the projects in this repository are END to END in the sense projects are done from scratch from data collection to deployment of the deep learning models.
User: gsaidheeraj
malaria-detection,MEDINFORM - AI Powered Multipurpose Web platform for Medical Image Analysis
User: guramritpalsaggu
Home Page: https://medinform.tk/
malaria-detection,Using tensorflow to predict if a cell is infected by malaria.
User: harirakul
Home Page: https://sites.google.com/view/malaria-detection/home?authuser=0
malaria-detection,CenterNet for Malaria parasites detection
User: hnmspirit
malaria-detection,Trained my first machine learning model using a public dataset of uninfected and parasitized cells images to detect malaria in humans with a low margin of error. Created a recursive model architecture with the following algorithm: image processing, grayscale conversion, contour detection, get areas of the 5 largest contours, and finally find the average of tumor area size of parasitized cells.
User: ishani-chakraborty
malaria-detection, This project utilizes TensorFlow to create a malaria detection model based on a modified LeNet architecture. It preprocesses the dataset, trains the model, and achieves accurate malaria detection with visualization.
User: itaynir1
Home Page: https://github.com/itaynir1/Malaria-Detection-by-Neuralearn-TensorFlow
malaria-detection,A basic GUI Malaria Diagnosis Tool (MDT) to help lab scientists find the probable type of malaria a patient may have based on the country they come form / country they are in.
User: jameswrc
malaria-detection,
User: kir486680
malaria-detection,Detecting Malaria Parasites in Red Blood Cells using Machine Learning (Specifically CNNs)
User: kjwharding
malaria-detection,Malaria classification app
User: lightknight64bit
Home Page: https://share.streamlit.io/lightknight64bit/malaria-classification
malaria-detection,Exploring image colour space transformations and augmentation for creating a classifier to characterise parasitized and uninfected RBCs. Proposes a CNN model that uses the Saturation of the HSV colour model to create a high quality classifier resulting in accuracies of 99.3% and above.
User: madhava20217
malaria-detection,To improve the accuracy and speed of malaria diagnosis, the project aims to distinguish Malaria infected human blood cells from the normal ones.
User: madhushree2000
malaria-detection,This repository contains a MATLAB project for malaria detection in microscopic images. It includes a MATLAB app and a standalone script that apply a malaria cell prediction algorithm. The project aims to assist in automating the detection of malaria cells, aiding in medical diagnosis and research.
User: mchinmayarao
malaria-detection,Malaria Detection Web App.
User: musstafa08-bug
malaria-detection,Malaria cells detection using CNN model.
User: mwoss
malaria-detection,EDoc is a medical web application. Where user can register and plan his diet chat based on his BMI and BMR analysis. User can also search about any disease or medicine with the help of integrated web scrapper. User also gets the functionality to check his malaria report by uploading his blood cell image.
User: namanadlakha3
malaria-detection, In this project, I implemented algorithms (VGG16, VGG19, and CNN) to develop a malaria detection system using blood cell images. The goal was to automate the traditional method of identifying malaria, which involves examining blood smears under a microscope.
User: nikhil-188
malaria-detection,Malaria-Detection using VGG-19.
User: officialnmn
malaria-detection,Malaria cell Binary Classification Probelm, Build DL Model USing Transfer learning technique.
User: pawarmukesh
malaria-detection,The GitHub repository presents an end-to-end case study on Malaria Disease Detection using CNN and Transfer Learning. The goal is to predict whether a given cell image is parasitized or uninfected.
User: princebari
Home Page: https://huggingface.co/spaces/Princebari/Malaria-Disease-Detection
malaria-detection,A menu based multiple chronic disease detection system which will detect if a person is suffering from a severe disease by taking an essential input image.
User: riturajsaha
malaria-detection,An efficient disease detection application with GUI based (tkinter) frontend and a custom CNN model as backend which detects if a cell is parasitized or normal from its image in real time with an accuracy of 95.22%.
User: riturajsaha
malaria-detection,Malaria Cell Detection using Pytorch
User: ritzing
malaria-detection,The repository contains the dataset of unknown variables and the script that is used to train this data
User: rukavishnikovmihail00
malaria-detection,The main task of this project was to predict whether a person has Malaria Disease or not.
User: salmaki-hub
malaria-detection,SANUS - A CADx Platform. To detect diseases with medical records.
Organization: sanus-ml
malaria-detection,Malaria is a life-threatening disease that is spread by the Plasmodium parasites. It is detected by trained microscopists who analyze microscopic blood smear images. Modern deep learning techniques may be used to do this analysis automatically. The need for the trained personnel can be greatly reduced with the development of an automatic accurate and efficient model. In this article, we propose an entirely automated Convolutional Neural Network (CNN) based model for the diagnosis of malaria from the microscopic blood smear images. A variety of techniques including knowledge distillation, data augmentation, Autoencoder, feature extraction by a CNN model and classified by Support Vector Machine (SVM) or K-Nearest Neighbors (KNN) are performed under three training procedures named general training, distillation training and autoencoder training to optimize and improve the model accuracy and inference performance. Our deep learning-based model can detect malarial parasites from microscopic images with an accuracy of 99.23% while requiring just over 4600 floating point operations. For practical validation of model efficiency, we have deployed the miniaturized model in different mobile phones and a server-backed web application. Data gathered from these environments show that the model can be used to perform inference under 1 s per sample in both offline (mobile only) and online (web application) mode, thus engendering confidence that such models may be deployed for efficient practical inferential systems.
User: sarkerrabi
Home Page: https://www.mdpi.com/2075-4418/10/5/329
malaria-detection,Malaria Parasite Detection using Efficient Neural Ensembles. Malaria, a life threatening disease caused by the bite of the Anopheles mosquito infected with the parasite, has been a major burden towards healthcare for years leading to approximately 400,000 deaths globally every year. This study aims to build an efficient system by applying ensemble techniques based on deep learning to automate the detection of the parasite using whole slide images of thin blood smears.
User: sauravmishra1710
Home Page: https://doi.org/10.35882/jeeemi.v3i3.2
malaria-detection,Using CNN to detect Malaria with the help of cell images
User: sayannath
malaria-detection,Web app for Malaria detection from the human blood sample images which is trained on National Library of Medicine dataset using Flask and Python.
User: sid321axn
Home Page: https://malaria-detection-app.herokuapp.com/
malaria-detection,A Sliding Window Approach for Malaria Detection in Thin Blood Film Images using Deep Learning
User: siddhanthp27
malaria-detection,ISEF 2023 (TEAM CANADA) PROJECT. Find the complete documentation and code in the README file linked here and below.
User: thetechdude124
Home Page: https://docs.google.com/document/d/154ejH2e1rFTS8mziY6jCYzXxh76EpW44_939VwtL3NI/edit?usp=sharing
malaria-detection,Malaria-Detection-Using-CNN
User: uzairhussain777
malaria-detection,A machine learning model and GUI for detecting Malaria in a cell.
User: we-gold
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