ITS70804 Text and Image Processing

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Assignment 3 — Mini Project (Weightage 30%)

AUGUST 2022 SEMESTER (BLOCK 1)

ITS70804

Text and Image Processing

Assessment Questions

(Assignment 3 is the continuation of Assignment 1. Therefore, students are advised to read the Assignment 1 and 3 documents side-by-side to understand and analyze the requirements properly).

 10-10 MySTIE Framework

Introduction

The Malaysian Science, Technology, Innovation, and Economic (MySTIE) Framework integrates ten key Malaysian socioeconomic drivers with ten global leading science and technology drivers that are aligned with our strengths and needs. This Framework lays out a systematic plan for transforming Malaysia into a knowledge-intensive economy by design (Academy of Sciences Malaysia, 2020).

Why is MySTIE important?

Science and technology must be linked to socioeconomic drivers in order to create value. The 10-10 MySTIE framework will allow Malaysia to combine science and technology with socio-economic drivers to spur national development. It hopes to improve Malaysian industries' competitiveness and sustainability by examining ten identified science and technology (S&T) drivers alongside ten critical socioeconomic sectors. In exchange, it should improve the quality of life for its citizens.

Advanced Intelligence Systems has been identified as a S&T driver that will add value and improve global competitiveness. Specifically, integration of text and image processing have been actively introduced as part of the solutions to MySTIE. Both of these fields are among the most active AI and machine learning research areas. However, before introducing a new system or service to the market or improving existing similar systems, businesses must conduct research to fully understand the challenges and specific needs to be addressed. As a result, applied research is introduced with the goal of developing scientific practical applications to solve practical and societal problems.

Reference:

10-10 Malaysian Science, Technology, Innovation and Economy (MySTIE) Framework. (2020, December 08). Retrieved from https://www.akademisains.gov.my/10-10-mystie


Your Big Idea and Deliverables

In this assignment, students are required to design text and image processing AI application as proposed in Assignment 1. MLO 2 and MLO 3 are evaluated through this assignment.

The tasks of Assignment 3 are stated as follows:

· Part 1: Introduction to System Architecture (10 marks).

Draw a flowchart / system architecture of the propose system/services in Assignment 1. Explain how the system/service works in addressing MySTIE Socio-economic drivers.

· Part 2: System Methodology (10 marks).

Development and implementation of the proposed system/service (text or image processing based). (Screenshots with Technical Description)

· Part 3: Results and Discussion (10 marks)

Performance evaluation using appropriate metrics. (Screenshots with Technical Description)

· Part 4: Conclusion and Future Work (Critical Discussion). (10 marks).

Describe how image or text processing can supplement and improve your system's functionality. What other socio-economic drivers might the system be able to address?

· Part 5: Demo and Presentation (10 marks)  Creative thinking skill and informative presentation.



Submission Requirements

1. Font type : Tahoma

2. Font size 11

3. Line spacing : 1.5

4. Alignment : Justify Text

5. Document type : .pdf. , .ipynb

6. Number of pages : 12 — 30 pages (do not exceed the page limit)

7. Your full report should consist of the following:

a) Cover page (Mini Project Title, Name, ID, Date, Signature, Score)

b) Marking Rubrics (attach as second page in the report)

c) Report of your answer script

d) Appendixes (line spacing = 1.0)

· List of references (APA format)

· Google Colab Python programming code (.ipynb)

· Report of similarity score (percentage of similarity score from each source needs to be shown)

8. Your answers/descriptions should be clearly labelled with the questions and sections they are in response to. For clarity, start each question/section on a separate page.

9. All figures and tables are labelled properly.

10. File naming conventions: StudentName_Assignment3.pdf

Notes:

· Student is not allowed to transcribe directly (cut and paste) any material from another source into their submission.

· Include in-text citation to support your answers and add the list of references at the end of your report (APA format). The list of references is to be alphabetized by the first author's last name, or (if no author is listed) the organization or title.

· The Turnitin similarity for this module is 20% overall and lesser than 1% from a single source excluding program source codes.


 

Marking Rubrics (lecturer’s use only)

Attach as second page in the report.

Question

Weight

Outstanding

(80 – 100)

Mastering

(65 – 79)

Developing

(0 – 64)

Part 1 Introduction

  /10

Description is clear, concise, and addressing the socio- economic driver(s) accurately. The flow chart / architecture diagram demonstrates comprehensive analysis of the model and recognise most consequences of solutions that articulates a reason for choosing a solution. The similarity is less than 2%.

Description is valid, and addressing the socio- economic driver(s) accurately. The flow chart / architecture diagram demonstrates enough evaluation of the model and recognise consequences of solutions that articulates a reason for choosing a solution. The similarity is between 2% to 4%.

Description is vague, and not addressing the socio- economic driver(s) accurately. The flow chart / architecture diagram

demonstrates enough evaluation of the model and recognizes some consequences of solutions that articulates a reason for choosing a solution. The similarity  is  greater  than  or

equal to 5%.

Part 2

System Methodology

  /10

Implement AI-based solution and monitor the process in a manner that addresses, thoroughly and in- depth, multiple contextual factors. Extend a novel text and image processing system to create new knowledge or knowledge that crosses boundaries. The similarity is less than 2%.

Implement AI-based solution and monitor the process in a manner that addresses multiple contextual factors. Create a novel or unique text and image processing system. The similarity is between 2% to 4%.

Implement AI-based solution and monitor the process in a manner that addresses limited contextual factors. Experiment with creating a novel or unique text and image processing system. The similarity is greater than or

equal to 5%.

Part 3

Results and discussion

  /10

Performance evaluation of the developed model with critical discussion and comprehensive explanation. The similarity is

less than 2%.

Performance evaluation of the developed model with brief explanation. The similarity is between 2% to 4%.

Performance evaluation of the developed model with limited

/ no explanation. The similarity  is  greater  than  or

equal to 5%.

Part 4 Conclusion

  /10

Appropriate conclusion with well explanation. The similarity is less than 2%.

Appropriate conclusion with moderate explanation. The similarity is between 2% to

4%.

Conclusion is made in a brief manner. The similarity is greater than or equal to 5%.

Part 5

Demo & presentation

  /10

Smooth and correct demo on pre-processing using Google Colab Python programming. Able to answer all questions from the examiners.

Not smooth but correct demo on pre-processing using Google Colab Python programming. Able to answer major questions from the examiners.

Not smooth and demo with minor error on pre-processing using Google Colab Python programming. Unable to answer most of the questions from the examiners.

Submission Requirements

  /10

Fulfil all submission requirements with excellent content organization.

Fulfil all submission requirements with consistent content organization.

Less obvious effort in compliance with submission requirement.



2022-10-14