Learning outcome
1.1

1.1 Comprehensive, theory based understanding of the underpinning natural and physical sciences and the engineering fundamentals applicable to the engineering discipline.
1.2

1.2 Conceptual understanding of the, mathematics, numerical analysis, statistics, and computer and information sciences which underpin the engineering discipline.
1.3

1.3 In-depth understanding of specialist bodies of knowledge within the engineering discipline.
1.4

1.4 Discernment of knowledge development and research directions within the engineering discipline.
1.5

1.5 Knowledge of contextual factors impacting the engineering discipline.
1.6

1.6 Understanding of the scope, principles, norms, accountabilities and bounds of contemporary engineering practice in the specific discipline.
2.1

2.1 Application of established engineering methods to complex engineering problem solving.
2.2

2.2 Fluent application of engineering techniques, tools and resources.
2.3

2.3 Application of systematic engineering synthesis and design processes.
2.4

2.4 Application of systematic approaches to the conduct and management of engineering projects.
3.1

3.1 Ethical conduct and professional accountability.
3.2

3.2 Effective oral and written communication in professional and lay domains.
3.3

3.3 Creative, innovative and pro-active demeanour.
3.4

3.4 Professional use and management of information.
3.5

3.5 Orderly management of self, and professional conduct.
3.6

3.6 Effective team membership and team leadership.
A1

<p>Apply digital imaging and artificial intelligence techniques in areas of robot vision, condition monitoring, quality control, environmental sensing and interaction, object recognition and classification</p>

A2

<p>Design, develop and optimize intelligent models based on artificial intelligence methodologies.</p>

A3

<p>Develop advanced learning algorithms for a neural network model to achieve the required design objectives.</p>

A4

<p>Implement the knowledge and skills gained through this subject in designing and developing intelligent mechatronics product / system.</p>

K1

<p>Demonstrate understanding of image processing, image representation, image segmentation, feature extraction and low-level image analysis techniques.</p>

K2

<p>Demonstrate understanding of spatial and frequency filtering.</p>

K3

<p>Interpret and analyse image analysis algorithms in edge and shape detection, colour based segmentation and image thresholding.</p>

K4

<p>Demonstrate understanding of pattern recognition and classification process.</p>

K5

<p>Explain and outline the advanced concepts and historical development of artificial intelligence.</p>

K6

<p>Interpret and discriminate the development of various optimization and machine learning algorithms / techniques.</p>

K7

<p>Demonstrate advanced understanding of expert systems and neural networks.</p>

S1

<p>Test and critically analyse results from the performed image analysis.</p>

S2

<p>Perform spatial and frequency filtering and feature extraction.</p>

S3

<p>Develop and analyse image analysis algorithms.</p>

S4

<p>Perform classification and pattern recognition using artificial intelligence and suitable methodologies.</p>

S5

<p>Evaluate optimization / network learning algorithms.</p>

S6

<p>Formulate and appraise fuzzy rules.</p>