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Learning from Demonstration, LfD Search Result 7
    • Ckip Lab

      Ckip Lab

      Textual Advertisement Generator: Given any limited specifics of any product, AI Advertisement Producer can automatically generate tons of top-quality descriptions and advertisements for the product in just one second. And not just one copy is produced. With deep learning and natural language processing technologies learned from millions of existing samples, our AI model can produce various styles of advertisements at the same time for users to select. It will be a big helper or a virtual brainstorming partner for any brands or advertisers to create their advertisements.
    • 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.
    • Advanced Machine Tools Research Center

      Advanced Machine Tools Research Center

      Tool wear and health condition monitoring during the processing: The tool wear monitoring technology developed by our researching team is specifically designed to analyze whether the tool is broken, collapsed, etc., and to estimate the remaining useful life(RUL) of the tool according to the working conditions of mass processing. By acquiring the vibration signal data with three-axis accelerometers installed on the machine tool, this technology could determine whether the current tool cutting vibration has exceeded the safety range by plotting a control chart. Once it exceeds the safe range, the current tool processing state will be assumed as abnormal. It gives users a reference to replace the broken tools immediately to prevent continuing processing, which causes vast loss such as poor quality of workpieces. In addition, this technology allows users to build models for distinct working conditions to predict the RUL of tools. It could allow users to evaluate the current health condition of tools and schedule the time to change the tool.
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