INT301 Bio-Computation 2020
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INT301 Assessment 1: Individual Report
1. Assessment Task (80 marks)
In this assessment, you are to implement MLP with back-propagation training algorithm using
MATLAB for vehicle logo classification. Please use sigmoid activation functions where necessary.
Be sure to design your program in a general, well-structured fashion, and document the code
appropriately.
A dataset (trafficsign.mat) is generated from an appropriate feature extraction algorithm on
detected traffic sign images. The six types of the digit images are shown in Fig. 1.
Fig. 1 Traffic sign images
For both MLP design, divide the dataset into a training set (80%) and a testing set (20%) and
show the convergence performance using MSE for each epoch in the training process.
Based on your algorithms designed, discuss the following in the report:
(1) For MLP: the effect of different number of hidden units (35 marks)
(2) For MLP: the effect of different learning rate and momentum (35 marks)
(3) Compare the best MLP model using confusion matrix (10 marks)
Note:
(1) It is acceptable to follow references (or using code fragments) from textbooks or internet
resources, but you must cite them clearly in your report;
(2) It is acceptable to apply Matlab toolboxes and Matlab functions.
2. Report (20 marks)
Each student must write an individual report in English. The report must be a single file in .pdf
format including all the plots, figures, tables and appendixes (failure to comply with this requirement
will be marked as Fail according 5. Marking Criteria).
The format of the report is: single-column A4 size, Times New Roman 12pt, single line spacing,
page numbered, 0.75-inch margin on top/bottom/left/right, and with maximum 5 pages including
cover page, reference (and appendixes if any).
The structure of the report is:
(1) Introduction: task description and background;
(2) Methodology: introduction of the methods and models;
(3) Experimental results and analysis: experiment procedures, results discussion and analysis,
performance comparison etc.;
(4) Conclusion;
(5) Reference.
INT301 Bio-Computation 2020
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3. Submission
You are required to:
(1) Compress your written report and source code into one single .ZIP file (other format such
as .rar or .7z will be marked as Fail according to 5. Marking Criteria);
(2) Name the zip file as: StudentID_GivenName_Surname (e.g. 1701234_Rui_Yang);
(3) Upload to the submission folder in ICE by 18:00, Sunday, Dec 20 2020.
Late submission will receive penalty in the marking in accordance with the University Code of
Practice on Assessment. For each working day after the deadline, 5 marks (out of 100) will be
deducted for up to 5 working days. However, the mark will not be reduced below the pass mark for
the assessment. Work assessed below the pass mark will not be penalized for late submission of up
to 5 days. Work received more than 5 working days after the deadline will receive a mark of 0.
4. Plagiarism
This assessment is an individual work. Plagiarism (e.g. copying materials from other sources
without proper acknowledgement) is a serious academic offence. Plagiarism will not be tolerated and
will be dealt with in accordance with the University Code of Practice on Assessment.
5. Marking Criteria
Category Requirement
First Class
(≥70%)
Overall outstanding work. All of the requirements have been implemented in the
program and report. Highly qualified report that closes to professional level. The report
is well-structured and organized, with all of required information included, with very
few English problems.
Second Upper
(60 to 69%)
Most of the requirements have been implemented in the program and report. Good
report which is clearly structured with most of the required information but with few
English problems.
Second Lower
(50 to 59%)
Substantial working program implementing a good range of the requirements.
Acceptable written report for Year 4 level, which contains sufficient information but
some English problems.
Third
(40 to 49%)
Executable program that generates recognizable results, which however are
incomplete. The written report is readable with insufficient information covered.
Problems may appear in the structure and organization, with many English problems.
Fail
(0 to 39%)
Wrong format in submission. Program is not working; or most of the required results
are not produced; or without acknowledging properly sources used if any. Poor report
which covers very limited number of items required.
No submission A mark of 0 will be awarded.
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