Advanced search

  • View:
  • Items
    • AI農情調查之UAV群眾協作平台

      AI農情調查之UAV群眾協作平台

      AI農情調查之UAV群眾協作平台後台支援自動鑲嵌建模,更具備四項突破技術:(1)巨量影像格化技術;(2)平行運算技術;(3)任務規格標準化;(4)UAV任務媒合。致力於打造空中UBER協作服務,未來能應用於農作物分佈調查、大範圍災情調查、農業保險、農地違法使用調查與休耕補助調查等面向。
    • Computer Vision Research Center, National Yang-Ming Chiao-Tung university

      Computer Vision Research Center, National Yang-Ming Chiao-Tung university

      Development of AI Platform for Smart Drone - Intelligent Flight: Due to its high mobility and the ability to fly in the sky, the drone has inspired more and more innovative applications/services in recent years. The goal of this project is to resolve the problem of blindly flying an unmanned aerial vehicle (UAV, which a drone in our case) when it is out of human sight or the range of wireless communication, and three major research and development directions will be considered in this project. Three artificial intelligence (AI) technologies, namely, smart sensing, smart control, and smart simulation, are applied in this project. Smart sensing - a flight system is developed, which can avoid the obstacles, complete a flight mission, and land safely. Smart control - an intelligence flight control system and a light-weighted somatosensory vest are developed. Smart simulation - a cost-effective training system and a 3D model simplification method are designed.
    • NCTU Sperm Sorter

      NCTU Sperm Sorter

      Infertility is a serious globe issue, especially in the developed countries, over 20infertile male has sperm problems, that include instance immotile, abnormal morphologylow sperm quantity. Therefore, how to isolate high quality sperm for clinical use is extremely required. Up to date, activity sperm sorting is usually using Swiming-upDensity gradient centrifugation approaches. Unfortunately, both methods are detrimental to the sperm viabilityelicits production of reactive oxygen species. Separation sperm by microfluidics has been put emphasis onstudied however, it faced some challenge such as low throughputan unacceptable recover rate.
    • MeDA Omni X-Ray (OXR): Real-time Hazard Identification System

      MeDA Omni X-Ray (OXR): Real-time Hazard Identification System

      “MeDA OXR: Real-time Hazard Recognition System,” which can automatically screen and interpret the medical images in real-time, is designed for emergency rooms to assist physicians in diagnosis, reducing medical risks, and improving overall efficiency. Combining portable X-Ray and AI algorithms, the system performs real-time and accurate preliminary screening and diagnoses of diseases, such as pneumothorax, pneumonia, and tuberculosis. It can also locate the nasogastric tube, endotracheal tube, and central venous catheter, while misplacement of that is sent to the physicians when detected.
    • DeepFIND

      DeepFIND

      Artificial Intelligence Automatic Sputum Microscopy System AIASMS: AIASMS can automatically shoot images from sputum smear samples and identify Mycobacterium tuberculosis(MTB). AIASMS can find the most suitable depth for shooting images and then automatically shoot images under the microscope through auto-focusing. These images will be stored in the cloud database. Meanwhile, AIASMS detect whether the sputum smear contains MTB. AIASMS can accurately label the location of the TB. The sensitivity and specificity can reach 90% and 99% respectively. We also cooperate with three hospitals in the northern, central, and southern regions of Taiwan to conduct blind testing, and the sensitivity can be more than 90%. AIASMS can also distinguish between MTB and Non-tuberculous mycobacteria (NTM). Finally, n the expansion of technology, we have extended the identification of the acid-resistant staining to the identification of gram staining, so that our system can widely identify a variety of bacteria.
    • ALOVAS

      ALOVAS

      ALOVAS Platform: ALOVAS acts as an A.I. Pathology Platform which provides high resolution pathology image viewer. Even Giga-pixel-level original images can be viewed online in real time. ALOVAS platform can be used not only on computer, but also on iPad. Users can upload images on the platform and select AI models for automated detection, and browse the detection results on the platform. ALOVAS also provides commonly used annotation tools, including hand-drawing, dots, rectangles, etc., which can be used to mark areas of interest. Embedded with the ALOVAS platform also provided several detection algorithms. We hope ALOVAS can assist physicians in rapid diagnosis, in related pathological research, and reduce the workload of pathologists in the future.
    • NTU CSIE Medical Informatics Lab

      NTU CSIE Medical Informatics Lab

      NTU Medical Genie Precision Health Platform: The product is mainly composed of wearable devices, IoT environmental sensors, deep learning, personal health app and case management platform. It can collect and monitor user's lifestyle and environment automatically, and predict the possibility of emergency to assist medical staff in making decisions. In addition, we opened source the project to solve most clinical studies that require lots of time to build data collection tools and processes.
    • alpha pulse

      alpha pulse

      ECG STEMI AI Model: In the past, most AI systems gave people the feeling of a black box and couldn't be trusted. The team designed a mechanism that allows doctors to adjust and observe the AI ​​model, so that the AI ​​model can be customized to the functions the doctor wants. We use LINE, the most commonly used communication software for doctors, to design an EKG Line Bot. Medical staff can upload an electrocardiogram to the EKG Line Bot to instantly identify whether the electrocardiogram is Stemi, so as to help doctors determine whether the patient has signs of myocardial infarction. We use this Line Bot to cooperate with doctors and ask them to communicate with the Line Bot. According to the heat map provided by the system, we can check whether it is consistent with the medical concept, and then help us correct the accuracy of our model. The system will train the correct data again.
    • Digital Medicine Center of National Yang Ming Chiao Tung University

      Digital Medicine Center of National Yang Ming Chiao Tung University

      AI-based Brain Assessment System: Mental illness is a critical health issue in Taiwan. Psychiatric diagnosis is largely based on self-reported or symptomatic criteria without objective findings. This state-of-the-art psychiatric diagnostic platform using standardized brain imaging data, however, improves the efficiency and accuracy of psychiatric diagnosis. Our platform can easily identify the deficiency in brain regions associated with schizophrenia, provides a novel way to evaluate mental illness and its progression, with powerful visualization. This web-based diagnostic platform has international multicenter validation, scientific publication, patent-pending as well as awarded by the 17th National Innovation Award in 2020, etc. This evidence-based, AI-assisted psychiatric diagnosis platform, validated with large-scale standardized brain imaging. We believe this state-of-the-art diagnostic tool can be a new light on modern psychiatric medicine, and promote mental health in the general population.
本網站使用您的Cookie於優化網站及您的購物經驗。繼續瀏覽網站即表示您同意本公司隱私權政策,您可至隱私權政策了解詳細資訊。