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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.
    • 3D Object Referring and Grasp Detection Networks

      AI & IOT Application FutureTech 3D Object Referring and Grasp Detection Networks

      "It is expected that human will work with robots in the coming years. However, it is still unknown how both can collaborate together. Meanwhile, it is still very time-consuming to deploy intelligent robots in production lines. For this work, we investigate deep comprehension for 3D (point cloud)text (voice) signals to enable novel human-robotic object referring for robotic arms. For the task
    • Visualization of brain connectomics: all-optical volumetric imaging/stimulation and spiking neural circuit models

      Excellence Research Center FutureTech Visualization of brain connectomics: all-optical volumetric imaging/stimulation and spiking neural circuit models

      Constructing a functional connectome and its computational model is a crucial step toward understanding the mechanisms of brain functions. To achieve this goal, we developed two correlated technologies: (1) An all-optical physiology (AOP) that is capable of millisecond volumetric imaging and accurate stimulation in living animal brains. This system allows us to establish functional connectome and neural coding with a single-cell resolution. (2) A cellular-level spiking neural circuit simulation system that is capable of tuning itself based on the input data from the AOP system. We have demonstrated our technologies in the Drosophila late visual system and will apply them in the brains of larger species such as mice. Our technologies will greatly enhance knowledge of brain operation.
    • Using 3-D Capsule Network for Nodule Detection in Lung CT Image

      AI & IOT Application FutureTech Using 3-D Capsule Network for Nodule Detection in Lung CT Image

      The computer-aided nodule detection system in CT image consists of the search sliding window, YOLOv2 architecture, 3-D CapsNet, skip connection,post-processing. First, the CT image is divided into numerous VOIs by sliding window. Second, a 3-D CapsNet based on YOLOv2 architectureskip connection is applied to the VOIs for classifying VOIs as nodulenot. Finally, the non-maximum suppression algorithm is performed to decide the final detection result.
    • free5GC: 5th generation mobile core network

      AI & IOT Application FutureTech free5GC: 5th generation mobile core network

      Although there are few open-source core network projects, none of them are conformed to 3GPP Release 15 (R15). The free5GC is the first one in the world based on 3GPP R15. The ultimate goal of free5GC is to implement a full commercial, operational core network including Operation, AdministrationManagement (OAM), orchestrator,network slicing complied with 3GPP R15beyond.
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