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技術研發單位
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    • Towards Automatic Hyperspectral Imaging via the Combination of Sample Navigation MappingLaser Scanning Spectral Microscopy

      Electronic & Optoelectronics FutureTech Towards Automatic Hyperspectral Imaging via the Combination of Sample Navigation MappingLaser Scanning Spectral Microscopy

      Photonic_Workshop@CCMS.NTU has successfully developed a motorized micro-mapping system to explore and navigate samples. This system is able to acquire high resolution images to produce a sample map automatically. This map is also synchronized with the coordinates of motorized stages. This achievement allows users to explore and position their hotspots from the map, and precisely deploy the hotspot to the central field of view by motorized stages. In addition, this mapping system can combine with a laser scanning confocal spectral microscope (LSCSM) to acquire sample spectral mapping. Our result has shown the capability to improve the efficiency of hotspot positioning and data acquisition process.
    • A Non-Invasive AI Imaging Technique for Quick Risk Assessment of Stroke and Cardiovascular Diseases

      Precision Health Ecosystem FutureTech A Non-Invasive AI Imaging Technique for Quick Risk Assessment of Stroke and Cardiovascular Diseases

      This product is a novel risk assessment tool for carotid artery stenosis and stroke. This is a revolutionary healthcare technology using motion analysis and quantification to extract information from pulses for risk assessments. The entire process is completed by taking a short video clip aimed at the neck with only one simple click on any mobile devices or our apparatus, anywhere, anytime. In less than five minutes, the user receives an evaluation report indicating low to high stroke risk. Our product accuracy stands higher than 90% when compared to the clinical outcome. The future indications of this product can be extended to arrhythmia, venous fistula obstruction, etc. This product has the great potential to achieve our dream of “personalized mobile hospital” in the future world.
    • Artificial Intelligent 3D Sensing Image Processing System for Array Sensing Lidar

      Smart machinerynovel materials FutureTech Artificial Intelligent 3D Sensing Image Processing System for Array Sensing Lidar

      High-accuracy 3D sensingAI image processing system for constructing high-quality immersion 3D image for AR/VR. Chaotic Lidar with APD arrayTOF sensors supports millimeter-accuracyinterference-avoiding capability. High-performance CNN processor supports high-performancelow DRAM bandwidth computations for various image AI applications.
    • Intelligent Image RecognitionAnalysis System for Small-sized Insect Pest

      AI & IOT Application FutureTech Intelligent Image RecognitionAnalysis System for Small-sized Insect Pest

      This study built an automatic insect pest image identification system based on tiny Yolov3 deep learning model. By optimizing the tiny Yolov3 detection model, images of insect pests on scanned sticky paper can be automatically identified. The system achieves a testing accuracy of 0.93, 0.90 for whitefliesthrips respectively.
    • Web-based Diagnostic System for Assessing Psychiatric Disorders

      AI & IOT Application FutureTech Web-based Diagnostic System for Assessing Psychiatric Disorders

      The Al-based web diagnostic system provides an online assessment tool for diagnosing schizophrenia. The Explainable Deep Neural Network classifier is deployed to analyze gray matterwhite matter to derive diagnostic classification of schizophrenia. The structural brain abnormalities associated with schizophrenia is visualized on the AI-based web diagnostic system at individual level.
    • 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.
    • Panchromatic CMOS TDI Image Sensor Design for Remote Sensing Satellite

      Electronic & Optoelectronics FutureTech Panchromatic CMOS TDI Image Sensor Design for Remote Sensing Satellite

      This project developed a CMOS Image Sensor (CIS) for the 2nd generation remote sensing satellite,its main achievement is to improve the ground resolution (also known as the Ground Sampling Distance, GSD) from 2 meters to sub-meter. The 12-cm large size chip of CMOS image sensor is implemented using Back-Side Illumination (BSI) CIS technology with mask stitching technologyutilizing the CMOS Time Delay Integration (CMOS TDI) technology in this design.
    • 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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