1 code implementation • 10 Oct 2019 • Gihan Jayatilaka, Harshana Weligampola, Suren Sritharan, Pankayraj Pathmanathan, Roshan Ragel, Isuru Nawinne
This paper presents a novel algorithm for the detection of sleep apnea with video processing.
no code implementations • 5 May 2020 • Suren Sritharan, Harshana Weligampola, Haris Gacanin
This paper studies practical limitations of learning methods for resource management in non-stationary radio environment.
no code implementations • 27 Jun 2020 • Harshana Weligampola, Gihan Jayatilaka, Suren Sritharan, Roshan Godaliyadda, Parakrama Ekanayaka, Roshan Ragel, Vijitha Herath
Low light image enhancement is an important challenge for the development of robust computer vision algorithms.
no code implementations • 21 May 2021 • Harshana Weligampola, Gihan Jayatilaka, Suren Sritharan, Parakrama Ekanayake, Roshan Ragel, Vijitha Herath, Roshan Godaliyadda
There is a lack of unsupervised learning approaches for decomposing an image into reflectance and shading using a single image.
no code implementations • 21 Aug 2021 • Umar Marikkar, Harshana Weligampola, Rumali Perera, Jameel Hassan, Suren Sritharan, Gihan Jayatilaka, Roshan Godaliyadda, Vijitha Herath, Parakrama Ekanayake, Janaka Ekanayake, Anuruddhika Rathnayake, Samath Dharmaratne
In this study, a forecasting solution is proposed, to predict daily new cases of COVID-19 in regions small enough where containment measures could be locally implemented, by targeting three main shortcomings that exist in literature; the unreliability of existing data caused by inconsistent testing patterns in smaller regions, weak deploy-ability of forecasting models towards predicting cases in previously unseen regions, and model training biases caused by the imbalanced nature of data in COVID-19 epi-curves.
1 code implementation • 13 Dec 2021 • Gihan Jayatilaka, Jameel Hassan, Suren Sritharan, Janith Bandara Senananayaka, Harshana Weligampola, Roshan Godaliyadda, Parakrama Ekanayake, Vijitha Herath, Janaka Ekanayake, Samath Dharmaratne
The system strives to holistically capture and interpret the information content of CCTV footage spanning multiple frames to recognize instances of various violations of social distancing protocols, across time and space, as well as identification of group behaviors.