SCSSE School of Computer Science and Software Engineering

Graduate Qualities

Teamwork

Function effectively in a multi-disciplinary/multi-cultural team as both a leader and a member. Understand the different roles and issues within a team.

Innovation and design

Discover innovative strategies to solve real world problems. Apply creative ideas to design and produce efficient and effective solutions using these strategies.

Informed

Have a sound knowledge of Computer Science or Software Engineering and understand its current issues, locally and internationally. Know how to apply this knowledge. Understand how this area of study has developed and how it relates to other areas.

Independent learners

Engage with new ideas and ways of thinking and critically analyse issues. Seek to extend own knowledge through ongoing research, enquiry and reflection. Find and evaluate information, using a variety of sources and technologies. Acknowledge the work and ideas of others.

Problem solvers

Take on challenges and opportunities. Apply creative, logical and critical thinking skills to respond effectively. Make and implement decisions. Be flexible, thorough and innovative and aim for high standards.

Effective communicators

Articulate ideas and convey them effectively using a range of media. Work collaboratively and engage with people in different settings. Recognise how culture and media can shape communication and be able to respond appropriately.

Responsible

Understand how decisions can affect others and make ethically informed choices. Appreciate and respect diversity. Act with integrity as part of local, national, global and professional communities.

Last reviewed: 15 October, 2008

Workshops and Seminars

Title: The Application of Microsimulation to Risk Modelling 

Speaker: Mr Duc Thanh Nguyen

Day: Wednesday 4/11/2009
Location
: Building 3. Common Staff Room
Time
: 11.30-12.30

Abstract: Abstract: Human detection from still images and videos is a crucial step of human motion analysis that currently receives much attention in computer vision area. This presentation is to provide a comprehensive review on recent developments of human detection and then present a detection method employing local contour-appearance features. Experimental results and comparison with other state-of-the-art human detection methods will be presented. Finally, trends and future directions will be indicated and discussed by way of posing some of the remaining key problems.

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