The department of Computer Engineering will be organizing a training on the topic entitled “Computer Vision and Applications” by Dr. Abubakar M. Ashir, which will take place between dates 27/03-07/04, 2022 at 03:00 PM in Laboratory Building Hall L.209.

Introduction: Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. It seeks to understand and automate tasks that the human visual system can do. It’s one of the most important conduits for information acquisition, decision making, and intelligence for most automated processes and applications. The training will provide a comprehensive explanation of both theoretical and practical implementation of computer vision and applications from the ground up.

Topics to be covered:

  • Computer Vision: Looking Back to Look Forward
  • Image/Video Formation and Acquisition for Computer Vision
  • Computer Vision Application Development with Python and Associated Libraries
  • Data Acquisition, Training, and web-based GUI with Streamlit
  • Transfer Learning for Computer Vision Development
  • Development of Biometric Face Recognition System with CNN
  • Object Detection with YOLO Object Detector
  • System Calibration, Measurement and Defect Detection in Object
  • Raspberry Pi Overview and Configuration
  • Raspberry Pi Headless Setup, IO Module programming, and CV Application Deployment
  • System Integration

Importance of Training:

Computer vision and its application are, without doubt, one of the most important fields that find applications in almost all nooks and crannies in our modern world. From transportation to agriculture, artificial intelligence to medical analysis, security to aviation, marketing to manufacturing, and many others. A few of the common applications of computer vision are listed below.

  • Face detection Systems
  • Autonomous Self-driving Car
  • Defect inspection
  • Product assembly
  • Pedestrian and Parking occupancy detection
  • Traffic flow analysis
  • X-Ray analysis
  • Products and customers sentiment analysis
  • Cancer detection
  • Aerial survey and imaging

Learning outcomes:

  • Participants will acquire both theoretical and practical knowledge and skills for implementing computer vision applications
  • Participants will acquire the know-how to participate in computer vision projects and careers.
  • Participants can be able to utilize the concept of transfer learning to easily develop computer vision applications.
  • Participants will learn how to develop a Graphical user interface for training and testing the computer vision algorithm.
  • Participants will learn the basics of working with hardware and microprocessor like raspberry pi and cameras
  • Participants will learn the process of image acquisition from a live streaming camera to the programming environment.
  • Participants will learn about working with Raspberry and how to deploy a computer vision program into Raspberry pi
  • Participants will learn about system integration i.e., combining the hardware (Raspberry pi, camera) and software (Computer Vision algorithm, GUI) into an application.

Registration Link: Click here to register (Seats are limited)