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Projet réalisé pour Leading Hospital (confidential) dans l'industrie Hôpitaux et Santé pour un public B2C en 2019.The goal of this project was to predict if a patient needed a pacemaker, based on an echocardiogram of the heart.
Collaboration en cours avec Sports streaming company (confidential) dans l'industrie Médias pour un public B2B / B2C depuis 2019.
Projet réalisé pour Saroléa Motorcycles dans l'industrie Automobile pour un public B2B / B2C en 2018. Performance and autonomy are extremely important to the commercial success of any electric vehicle. Saroléa develop high-performance electric vehicles with their flagships being their electric superbikes: the MANX7 and the recent N60. These bikes are equipped with the latest in technology, including high frequency sensors and Saroléa’s own vehicle control unit which has recorded a massive amount of data over the course of several years. Saroléa want to leverage this data to optimize their bikes, and ultimately to offer this as an add-on package for the vehicle control unit.
Projet réalisé pour De Volksbank dans l'industrie Banque et Finance pour un public B2B / B2C en 2020.We did a risk assessment for giving a loan to a specific customer. Every Dutch bank has to report to the De Nederlandsche Bank (DNB). One of these reports is the quarterly Residential Real Estate (RRE) report, which is an initiative to gain information of financial institutions about their residential real estate loans on a granular and regular basis. All banks are struggling to gain control of the quality of the data in these reports. ML6 helped De Volksbank with setting up anomaly detection analysis and dashboarding. First, this should give them a feeling of the amount of divergent or “to be checked”- data by applying unsupervised learning. Second, after De Volksbank checked and categorised a sample of these anomalies, we continued with supervised learning to show what amount of errors in what category they could expect.
Projet réalisé pour AVROTROS dans l'industrie Médias pour un public B2B / B2C en 2020.Video parsing of news bulletins to extract context from spoken text and the text visualized on the screen. summarizing of content.
Projet réalisé pour Confidential dans l'industrie Produits ménagers pour un public B2B / B2C en 2019.The customer is one of the leading rug manufacturers in Europe. The system at the customer requires a trial and error phase to determine the correct folding line each time the rug type is changed. This is both a cumbersome and time consuming task. Our goal is to automate this task by using computer vision to detect the folding line, saving the customer a lot of time while also reducing the amount of human input.