Pinned Repositories
advanced-markdown
Learn about advanced markdown techniques
Biomedical_Wearable_Group_6
Project of Group 6 composed by Alessio Lerede, Martina Sapone and Claudia Tarricone for "Biomedical wearable TECHNOLOGIES FOR HEALTHCARE AND WELLBEING 21/22" course. This app provides fetch of Activity and Heart data from a database linked to FitBit and contains a: -Activity Page where is shown the step distance covered in the last 7 days. In addition to this Page, for every distance covered, is possible to have suggestions about the food to eat in order to be always in good shape! -Heart Page where is shown the heart rate monitoring in the last 7 days. -Calendar Page where you can organize all your activites. -Workout Page which contains a personalized workout program to burn more calories as possible. -Profile Page where all the User's information are stored. To use this app, you are obliged to consent the authorization of your own data. This is required to make your app useuful and ensuring the security of your data. Enjoy your fitness activity! MonJour! ☀️
Brain-MRI-tumor-segmentation
Medical image processing is the most challenging and emerging field now a days. Processing of MRI images is one of the part of this field. This paper describes the proposed strategy to detect & extraction of brain tumour from patient’s MRI scan images of the brain. This method incorporates with some noise removal functions, segmentation and morphological operations which are the basic concepts of image processing. Detection and extraction of tumour from MRI scan images of the brain is done by using MATLAB software.
dedalus
A flexible framework for solving PDEs with modern spectral methods.
monheritier
Named-Entity-Recognition-for-Biomedical-Domain-NER-model-
NLP-Task-on-Tweet
Evaluate the text and classify the type of disaster from a twitter dataset
Tech-Test-ML-Coin
monheritier's Repositories
monheritier/Biomedical_Wearable_Group_6
Project of Group 6 composed by Alessio Lerede, Martina Sapone and Claudia Tarricone for "Biomedical wearable TECHNOLOGIES FOR HEALTHCARE AND WELLBEING 21/22" course. This app provides fetch of Activity and Heart data from a database linked to FitBit and contains a: -Activity Page where is shown the step distance covered in the last 7 days. In addition to this Page, for every distance covered, is possible to have suggestions about the food to eat in order to be always in good shape! -Heart Page where is shown the heart rate monitoring in the last 7 days. -Calendar Page where you can organize all your activites. -Workout Page which contains a personalized workout program to burn more calories as possible. -Profile Page where all the User's information are stored. To use this app, you are obliged to consent the authorization of your own data. This is required to make your app useuful and ensuring the security of your data. Enjoy your fitness activity! MonJour! ☀️
monheritier/Brain-MRI-tumor-segmentation
Medical image processing is the most challenging and emerging field now a days. Processing of MRI images is one of the part of this field. This paper describes the proposed strategy to detect & extraction of brain tumour from patient’s MRI scan images of the brain. This method incorporates with some noise removal functions, segmentation and morphological operations which are the basic concepts of image processing. Detection and extraction of tumour from MRI scan images of the brain is done by using MATLAB software.
monheritier/advanced-markdown
Learn about advanced markdown techniques
monheritier/dedalus
A flexible framework for solving PDEs with modern spectral methods.
monheritier/monheritier
monheritier/Named-Entity-Recognition-for-Biomedical-Domain-NER-model-
monheritier/NLP-Task-on-Tweet
Evaluate the text and classify the type of disaster from a twitter dataset
monheritier/Tech-Test-ML-Coin