diff --git a/README.md b/README.md index aee8b26..aeffb03 100644 --- a/README.md +++ b/README.md @@ -1,15 +1,15 @@ # Table of Contents -1. [A Gentle Introduction](#orgf9d4f1c) - 1. [Lecture Information](#org33b5f32) - 1. [Assignments](#orgf7e9b9e) - 2. [The Lecture Structure](#orgb5cae0e) - 3. [Code Supplement](#org94a0f06) - 4. [Reading List](#org159a80f) +1. [A Gentle Introduction](#org6bdbe1a) + 1. [Lecture Information](#orga66fad8) + 1. [Assignments](#org8ab78d2) + 2. [The Lecture Structure](#org6649915) + 3. [Code Supplement](#org1715c47) + 4. [Reading List](#orgddf167e) - + # A Gentle Introduction @@ -22,7 +22,7 @@ focus will be on the topics of: 4. An example of using ML in image recognition techniques. - + ## Lecture Information @@ -118,7 +118,7 @@ The details of the lecture are given below. - + ### Assignments @@ -161,135 +161,135 @@ The grade breakdown is as follows: -1. Individual Assignment - - An individual assignment will be given to you to work on. This assignment will consist of - questions pertaining to concepts and image processing techniques. - - The grade breakdown is as follows: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
DEFINITIONGRADE (%)
Report Style15
Q1 - Blurring Filters15
Q2 - Image Channel Analysis15
Q3 - RNG Map Generation10
Q4 - Image Cleaning10
Q5 - Shape Recognition30
Q6 - Image Quality Comparison10
Sum100
- - **NOTE:** The assignment is individual and is not meant to be worked as a group. Once the - code and the work is submitted it will be vetted against a software to determine - if any collusion has occured. - -2. Group Assignment - - The group assignment focuses on a student defined project which its presentation will be - done in the last 3 sessions of the course. You are to come up with a group and a project - within the first 3 weeks of the lecture otherwise one will be given to you. - - The grade breakdown is as follows: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
DEFINITIONGRADE (%)
Report Style15
Content55
Q & A30
- - In report writing students must declare their contribution to the work and they will be - asked regarding their field of work during the Q&A (i.e., if Student A has worked with - blurring filter he may be asked on why a specific one is chosen and/or the concepts and - maths behind the said filter). - - **NOTE:** Students will be graded based on their contribution to the project and answers - during the Q&A, therefore will be graded individually. - - - +**Individual Assignment** + +An individual assignment will be given to you to work on. This assignment will consist of +questions pertaining to concepts and image processing techniques. + +The grade breakdown is as follows: + + + + +++ ++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
DEFINITIONGRADE (%)
Report Style15
Q1 - Blurring Filters15
Q2 - Image Channel Analysis10
Q3 - RNG Map Generation10
Q4 - Image Cleaning10
Q5 - Shape Recognition30
Q6 - Image Quality Comparison10
Sum100
+ +**NOTE:** The assignment is individual and is not meant to be worked as a group. Once the +code and the work is submitted it will be vetted against a software to determine +if any collusion has occured. + +**Group Assignment** + +The group assignment focuses on a student defined project which its presentation will be +done in the last 3 sessions of the course. You are to come up with a group and a project +within the first 3 weeks of the lecture otherwise one will be given to you. + +The grade breakdown is as follows: + + + + +++ ++ + + + + + + + + + + + + + + + + + + + + + + + + + +
DEFINITIONGRADE (%)
Report Style15
Content55
Q & A30
+ +In report writing students must declare their contribution to the work and they will be +asked regarding their field of work during the Q&A (i.e., if Student A has worked with +blurring filter he may be asked on why a specific one is chosen and/or the concepts and +maths behind the said filter). + +**NOTE:** Students will be graded based on their contribution to the project and answers +during the Q&A, therefore will be graded individually. + + + ## The Lecture Structure @@ -432,7 +432,7 @@ methods in improving/analysing gathered images. The structure of the lecture is - + ## Code Supplement @@ -442,7 +442,7 @@ it is not feasible to fit all the content of the code to the slides and it is ea [Visit the Code Supplement Website](https://dtmc0945.github.io/L-MCI-BSc-Digital-Image-Processing/) - + ## Reading List @@ -456,5 +456,3 @@ mandatory. 3. Nixon M. et. al "Feature Extraction and Image Processing for Computer Vision" Academic press 2019 4. Gonzalez R. "Digital Image Processing" Pearson 2009. -**White Papers** -