The UoM team won the 1st runner up award in the signal processing cup (SP Cup) 2020 competition attached to the International Conference on Acoustics, Speech, and Signal Processing (ICASSP), virtually held in Barcelona, Spain, from May 4 to 8, 2020. The winning team comprised of six undergrads of the Department of Electronic and Telecommunication Engineering (ENTC), and four undergrads of the Department of Computer Science and Engineering. Mr. Dumindu Tissera (a Ph.D. candidate of the ENTC) tutored and the team and Dr. Chamira Edussooriya (ENTC) supervised the team.
The SP Cup competition is an annual event organized by the IEEE signal processing society to encourage students to solve real-world problems using signal processing techniques. It is held as a sub-event of the ICASSP, which is the world’s largest and most comprehensive technical conference focused on signal processing and its applications, with more than 1500 research paper presentations each year.
This year’s SP Cup challenge was on “unsupervised abnormality detection by using intelligent and heterogeneous autonomous systems.” The UoM team employed a blend of signal processing techniques and state-of-the-art machine learning techniques, such as long short-term memory and conditional generative adversarial networks, to detect abnormalities (i.e., unusual or suspected events) using inertial measurement unit (IMU) sensor data and video data captured by the cameras of autonomous systems, e.g., drones. The proposed solution by the UoM team achieved 98% accuracy with IMU sensor data and 95% accuracy with video in detecting anomalies in the dataset provided for the competition. In the first round, the UoM team scored the highest among the participated teams from all around the world. In the final presentation, the team from the Technion - Israel Institute of Technology, Israel surpassed the UoM team.
Signal processing---" analyzing, modifying, and synthesizing signals such as sound, images, and scientific measurement”--- is an important field in today’s information-rich world. This coveted achievement places the UOM within a substantial place in the signal processing community. The challenge is to continue excelling in the area of signal processing.