Instructor

B.K.Mohan

Semester

Spring ‘20

Course Difficulty

The course is easy to follow

Time Commitment Required

1 or 2 hours besides lecture

Grading Policy and Statistics

Lenient , easy to score BB or better with minimal efforts

Attendance Policy

None

Pre-requisites

None but a machine learning course would be quite helpful

Evaluation Scheme

There were 3 quizzes with 5% weightage each, a paper review and programming assignment (25%),midsem (20%) and endsem (40%)

Topics Covered in the Course

The course begins with basics of Satellite images and multispectral images, then some basic algorithms used in image processing were discussed. Some algorithms like K-SOM which are not conventionally used were also taught and towards the end, the machine learning approaches were taught

Teaching Style

The professor uses slides to teach and explains the concepts quite well.

Tutorials/Assignments/Projects

The project involves implementation of some algorithm taught in the course

Feedback on Exams

The quizzes consisted of 5 one mark questions and were generally easy and based on direct statements in the slides
The midsems and endsems contained bigger questions but were still directly based on slides . Generally questions like explain a particular algorithm and mention it’s advantages and disadvantages were asked. All questions were non numerical

Review By: Kaustubh Ponkshe