The department of Computer Engineering has organized a training on the topic entitled “Computer Vision and Applications” by Dr. Abubakar M. Ashir. The training was held between the dates 27/03 – 31/03 and 08/05 – 12/05/2022 at 03:00 PM in Laboratory Building Hall L.209.

Computer vision is an interdisciplinary scientific field that deals with how computers can gain a 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.

The training aimed to highlight the concepts of computer vision and its applications, which are, without doubt, one of the most important fields that exists 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

  • 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

Each training session delved into one of the following topics:

  • 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

The participants were able to acquire both theoretical and practical knowledge and skills for implementing computer vision applications, the know-how to participate in computer vision projects and careers. The participants were also exposed to process of image acquisition from a live streaming camera to the programming environment. Participants also learned how to develop a Graphical user interface for training and testing the computer vision algorithm. The basics of working with hardware and microprocessor like Raspberry Pi and cameras were also highlighted along with the steps to deploy a computer vision program into Raspberry pi along with combining the hardware (Raspberry pi, camera) and software (Computer Vision algorithm, GUI) into an application.

The department of Computer Engineering extends its gratitude and appreciation to Dr. Ashir for the beneficial training and for the participants for their valuable attendance.