Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019).

The overall objective of this Engage project is to improve digital video wireless communication experience byx000D
utilizing deep learning based super-resolution. This goal will be achieved by developing deep learning basedx000D
algorithms for video down-sampling at transmitter and video super-resolution at receiver. Moreover, we willx000D
use new deep learning methods to optimize the entire parameter selection process of a video encoder based onx000D
frame data and wireless link quality to achieve the best rate-distortion performance. The deep learning basedx000D
down-sampling and super-resolution algorithms will be able to generate high resolution videos underx000D
dramatically changing communication bandwidth, significantly enhance the performance of video encoding forx000D
wireless communication, and therefore provide high quality videos under harsh wireless communicationx000D
environments such as in forest, underground and in dense cities. The research achievement will definitelyx000D
contribute to video super-resolution and wireless video transmission, which will benefit Canadian wirelessx000D
industry in huge vertical markets such as video monitoring and surveillance, remote healthcare and smartx000D
senior homes, public safety and environment monitoring.