進階篩選

Technical category
技術研發單位
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    • Applying Machine Learning to User Mobility Type Identification for 5th Generation Mobile Networks

      AI & IOT Application FutureTech Applying Machine Learning to User Mobility Type Identification for 5th Generation Mobile Networks

      Due to the fast development of 5G networks, it is critical to identify users service types to allocate resources intelligently. Our technology focuses on users' mobility type identification by extracting practical features from users' cellular information. We proposed a system architecture and have collected 700-hour data with 150 GB. By using our data and other datasets in the world, we show that our technology can achieve 95% accuracy, and reduce 16% energy consumption compared to traditional methods.
    • Building A Deep Learning-based Chest X-ray CADe Platform MedCheX

      Precision Health Ecosystem FutureTech Building A Deep Learning-based Chest X-ray CADe Platform MedCheX

      As we continue to face the rapid increase in confirmed Coronavirus cases around the world, we created an AI-based pneumonia detection platform for COVID-19. The system is able to automatically detect high-risk patients with pneumonia that will then send information to doctors. With that information, the doctors are then able to make follow-up decisions and provide a treatment plan after the diagnosis. In specific, doctors from the Department of Medical Imaging provided us thousands of positive and negative chest x-rays for pneumonia as a training set. Our system has already been tested with and adopted by doctors at the NCKU Hospital. The system achieved 95% accuracy to detect the pneumonia symptom, based on 1400 test images.
    • To develop a Guidance Robot for Blind based on image processingdeep learning

      AI & IOT Application Innotech Expo To develop a Guidance Robot for Blind based on image processingdeep learning

      This theme is designed to implement the robot's appearancepractical functions. Apply PSPNet to detect the walkable planeYolo to detect obstacles, so that the robot has the autonomous obstacle avoidance function, informing more information about the environmental obstacles around the visually impaired,apply CNN to locate indoor position with self-built indoor database.
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