Machine Learning and Image Processing
Machine Learning and Image Processing, Virtual Short Course in Future Technology Week 2. Telkom University is proud to collaborate with the University of Kuala Lumpur Malaysia and Mapua University Philippines in organizing an online joint class Virtual Short Course in Future Technology. This virtual class entitled Machine Learning and Image Processing is the second class after the first-class last week.
Today’s Class of Machine Learning and Image Processing, October 16, 2021, consists of two sessions and invites two experts from the University of Kuala Lumpur and Mapua University. Dr. Madhavi Devaraj from Mapua University presented Artificial Intelligence and Dr. Rasheed from the University of Kuala Lumpur presented Image processing. Both are expert lecturers in the fields of Machine Learning and Image Processing.
Machine Learning and Image Processing in Artificial Intelligence Era
Opening the first session of the class of Machine Learning and Image Processing, Dr. Madhavi Devaraj explains that machine learning is a branch of artificial intelligence (AI) and computer science that focuses on using data and algorithms to imitate the way humans learn and gradually increase their accuracy. Machine learning is an important component of the field of science about data development. Unlike Artificial Intelligence, machine learning cannot think on its own.
In this first session of machine learning and image processing, Dr. Madhavi also explained about Deep Learning which is a subset of machine learning. Deep Learning is essentially a neural network with 3 or more layers. It is a technique which mimics the human brain. The neural network attempts to simulate the behaviour of the human brain.
In addition, in the current era of artificial intelligence, Image processing is an important science. In the second session of machine learning and image processing, Dr. Rasheed explains about how Image Processing works and its advantages, and it’s connection to machine learning. Image Processing is carried out to correct image signal data errors that occur due to transmission and during signal acquisition, as well as to improve the quality of image appearance so that it is more easily interpreted by the human vision system.
The class of machine learning and image processing was closed by some questions from students and assigned students to join the breakout room for strengthening the material by the lecturers. After this machine learning and image processing class, there will be other advanced classes. Keep following our social media for other interesting class information.(IO)***