Instructional Objectives: (1)Combined with the development practice of edge computing; applied to training in data engineering, data analysis, data science, machine learning algorithms and other related fields; (2)Conduct industrial control security architecture training and actual combat simulation training.
Hands-on Course: Deep Learning Program Practice, Artificial Intelligence Technology Practice, Hyper-heuristic Algorithm, Edge Computing Practice, Industrial IoT Information Security Threat Detection and Protection, PUF Information Security Technology
Experimental Device: AI computing server, AI computing workstation, Edge computing development teaching system and Cyberbit OT ground hardware
Laboratory for AI IoT
Location: Machine Tool College Building
Instructional Objectives: Combined with the Intelligent Internet of Things (AIOT); applied to training in artificial intelligence-related fields such as intelligent manufacturing and intelligent robotic arms.
Hands-on Course: AIoT Control Practice, Data Acquisition and Sensor Practice, Industrial Internet of Things, Internet of Things Communication Practice
Experimental Device: AIoT development teaching system
Laboratory for AI Robot
Location: Guo Xiu Building
Instructional Objectives: (1)Realize ROS artificial intelligence development practice training as the main axis, and apply it to training in related fields such as smart wearable devices, smart search, and smart robots; (2)Amazon AI racing development practical training
Hands-on Course: AI Robotics, AI Image Recognition Practice, AI Computer Vision Practice, Deep Learning Program Practice, Artificial Intelligence Technology Practice, Hyper-heuristic Algorithm, Edge Computing Practice
Experimental Device: ROS artificial intelligence development teaching system; Amazon AI racing teaching system
Smart Imaging Lab
Location: Guo Xiu Building B1F-KB105
Instructional Objectives:(1) Develop medical image recognition and apply it to the analysis of various medical imaging data. Through automated analysis of lesions in images, and through continuous development of new algorithms and models, it can be applied to various applications such as disease detection, further promoting medical technology innovation and breakthroughs.
(2) Develop image recognition applications, including smart cities and security monitoring, public safety monitoring systems, industrial automation, etc. In manufacturing, image recognition technology is used to detect product defects, quality control, and production line monitoring.
Hands-on Course:
Smart Medical Image Processing, Smart Life Image Application Practice, AI Image Recognition Practice, OpenCV Image Processing Practice, Introduction to Computer Vision, Robot Vision Practice
