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Learning how societies around the world feel during a viral outbreak in real time
Would the average rating of your movie (or TV-show) beat the average? This Dockerized Machine-Learning Webapp gives an educated guess based on the analysis of over 300,000 real titles.
AI based COVID-19 Detector system that can early detect whether the patient is COVID Positive or not by using chest X-ray images of patient.
Modellierung der Tourismusströme in Europa und deren Einfluss auf die Ausbreitung von SARS-CoV-2
Development of an ML tool for data visualization of current data in different graphs. Possible extension to forecasts based on already past data.
Erstellung eines räumlich-zeitlichen Modells für die Ausbreitung von COVID-19 und die Bewertung der Auswirkung auf die Bevölkerung und Wirtschaft.
Segmentation Neural Network detects burned areas after wildfires on satellite images so the state can respond thanks to reliable data quickly, and experts can spend less time on primary analysis.
Using the retina images of the eye, it can detect the possibility of diabetes in a person with the help of Pytorch
There a lot of time when we are not connected to internet and therefore we can't find the actual path to our destination. But in this project we can find optimized path using AI with previous data
CovidScan.ai is developed to be a secured AI platform with the purpose to assist radiologists with fast and accurate pneumonia dectection amid this COVID-19 pandemic.
Model based on statistics of each player in the team, such as goals, goals in first period, goals in second period, home games, etc.
Based on a selfie, a predicted emotion is an output to a recommender system that gives suggestions of places to go and things to do.
A platform for displaying and optimizing literary searches for the modern geneticist.
HOWL uses machine learning to manipulate coyote behaviour for the purposes of coyote population control. HOWL seeks to save farmers and taxpayers millions and protect suburbs.
a scene from a machine imagined myth
Most hospitals match patient data manually, and computer programs achieve about 90% accuracy. We have developed a machine learning algorithm to automatically match patients with 95% accuracy.
Detects atopic eczema in babies. Used by 3rd-world midwifery nurses.
Nopanic.io aims to provide contextual information in order to help contain the COVID19 outbreak. This web app provides guidelines based on the user's location to help them navigate the outbreak.
Vaughn explores the data and discusses ideas for how anomalies can be detected.
Combining our passion of exercise and gaming, we decided to make a game in which one progresses through real life fitness progress, recorded by Strava.
Our idea is to use data analytics in order to better process the data, find relationships between channels, and then attempt to reduce the costs of operation after identifying duplicate sensors.
In this project we propose a method for detecting sensor anomalies in time-series data based on the difference between the predicted and actual output of a sensor
A product which increases efficiency when it comes to using energy, reducing the amount of waste produced and money spent
Too busy for Tinder? With RU Single, you can train a model to learn what kind of faces you're attracted to and then use a bot to automatically swipe left or right depending on your past swipes.
