| CODE | CCE5500 | |||||||||
| TITLE | Research Topics in Signal Processing and Machine Learning | |||||||||
| UM LEVEL | 05 - Postgraduate Modular Diploma or Degree Course | |||||||||
| MQF LEVEL | Not Applicable | |||||||||
| ECTS CREDITS | 6 | |||||||||
| DEPARTMENT | Communications and Computer Engineering | |||||||||
| DESCRIPTION | In this study-unit the student carries out desktop research (via selected readings from relevant publications) in a chosen topic of signal processing and machine learning, including specific application areas. The topics are offered by various members of staff and can change from year to year. Topics include but are not limited to: - Automated Assessment; - Speech and Audio Processing; - Digital Communications; - Design Automation; - Probabilistic Shape models; - Image Forensics; - Gesture recognition; - Medical Informatics; - Multiview Signal Processing. To assist students with their reading, regular meetings are held with the academic concerned to discuss the progress and any problems encountered. These meetings are reported in a research logbook which is updated regularly and signed by the student and the lecturer. Once the student has read sufficiently, he or she is expected to draw up a long essay which reviews the texts under consideration and draws pertinent conclusions. The review is expected to offer a mature discussion, comparing and contrasting the works within a sensible framework and an indication of the way forward. Study-unit Aims: The aim of this study-unit is to expose the students to state of the art research papers in the area of 'Signal Processing and Machine Learning', help them organise their reading and research efforts while also giving them the opportunity to write a literature review. This will give the students invaluable background in the topic selected while also giving them the opportunity of hands on research under close guidance from the academic. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will: - Have a comprehensive appreciation of advanced state-of-the-art topics in selected topic within the area of 'Signal Processing and Machine Learning'; - Be able to outline the research landscape of the topic selected and explain how different aspects of the topic relate to one another. 2. Skills: By the end of the study-unit the student will be able to: - Discuss and critically analyze research papers covering current open problems in the field; - Search for literature covering background and related work and summarize them into a literature review. Main Text/s and any supplementary readings: Selected readings from: - Examples of Review Papers. - Bengio, Y.; Courville, A.; Vincent, P., "Representation Learning: A Review and New Perspectives," Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol.35, no.8, pp.1798,1828, Aug. 2013. - Suarez, J.; Murphy, R.R., "Hand gesture recognition with depth images: A review," RO-MAN, 2012 IEEE , vol., no., pp.411,417, 9-13 Sept. 2012. Jinyu Li; Li Deng; Yifan Gong; Haeb-Umbach, R., "An Overview of Noise-Robust Automatic Speech Recognition," Audio, Speech, and Language Processing, IEEE/ACM Transactions on , vol.22, no.4, pp.745,777, April 2014. [Available with the IEEE UoM subscription]. - C.Romero and S. Ventura, "Educational Data Mining: A Review of the State of the Art", IEEE Transactions on Systems, Man, and cybernetics -Part C, vol.40, no.6, November 2010. - Jungong Han; Ling Shao; Dong Xu; Shotton, J., "Enhanced Computer Vision With Microsoft Kinect Sensor: A Review," Cybernetics, IEEE Transactions on , vol.43, no.5, pp.1318,1334, Oct. 2013. - Malassiotis, S.; Tsalakanidou, F., "Recognizing facial expressions from 3D video: Current results and future prospects," Automatic Face & Gesture Recognition and Workshops (FG 2011), 2011 IEEE International Conference on , vol., no., pp.597,602, 21-25 March 2011. - Kotsia, I.; Zafeiriou, S.; Fotopoulos, S., "Affective Gaming: A Comprehensive Survey," Computer Vision and Pattern Recognition Workshops (CVPRW), 2013 IEEE Conference on , vol., no., pp.663,670, 23-28 June 2013. |
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| STUDY-UNIT TYPE | Lecture and Independent Study | |||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Adrian F. Muscat |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2023/4. It may be subject to change in subsequent years. |
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