進階篩選

Technical category
技術研發單位
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    • Advancement Project for Smart Machinery and Aerospace Industries in Central and Southern Taiwan

      FutureTech Advancement Project for Smart Machinery and Aerospace Industries in Central and Southern Taiwan

      The developed technology is a cross-platform interface demonstrates its capabilities via the machining center VP2012. The interface is able to synchronize operating systems for diversified controllers. It integrates multiple functions, such as intelligent thermal balance, intelligent vibration analysis, and artificial neural network learning responsive technique. The developed technology advances software, hardware and firmware of a MIT machining center, setting up a representative example of smart machine for local manufactures, even the whole industry.
    • Development of cutting knowledge base to enhance machine tool performance

      Smart machinerynovel materials FutureTech Development of cutting knowledge base to enhance machine tool performance

      "Tool replacementtool life diagnosis" in smart manufacturing is a key link between the quality of workpiecethe efficiency of the manufacturing process, so it is an indicator of the operating efficiency of machine tools. This technology combines on-site monitoring data, laboratory analysisdeep learning to provide best tool selectionprocessing parameter combinations for
    • 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.
    • Efficiency Boosting System for Computer Numerical Control Milling Machine Based on AIBig Data Analytics

      AI & IOT Application FutureTech Efficiency Boosting System for Computer Numerical Control Milling Machine Based on AIBig Data Analytics

      This technique combines more than one AI models to precisely predict current under noisy data from current sensoroptimizes speed rate based on this AI forecasting model. At the same time, it considers the practical requirementslimitations of workpiece surface roughness, tool machine current load, etc. This technique provides decision supports for optimizing parameters of CNC milling machine to keep high efficiencyenhance energy conservation.
    • 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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