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20202026
most citedToward Interpretable Sleep Stage Classification Using Cross-Modal Transformers

53 citations · 78 across the 28 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.AR2021

Kraken: An Efficient Engine with a Uniform Dataflow for Deep Neural Networks

G Abarajithan, Chamira U. S. Edussooriya

Deep neural networks (DNNs) have been successfully employed in a multitude of applications with remarkable performance. As such performance is achieved at a significant computation…

cs.CV2021

PointCaps: Raw Point Cloud Processing using Capsule Networks with Euclidean Distance Routing

Dishanika Denipitiyage, Vinoj Jayasundara, Ranga Rodrigo +1

Raw point cloud processing using capsule networks is widely adopted in classification, reconstruction, and segmentation due to its ability to preserve spatial agreement of the inpu…

cs.CV2021

Towards Accurate Cross-Domain In-Bed Human Pose Estimation

Mohamed Afham, Udith Haputhanthri, Jathurshan Pradeepkumar +3

Human behavioral monitoring during sleep is essential for various medical applications. Majority of the contactless human pose estimation algorithms are based on RGB modality, caus…

eess.SP2021

WLS Design of ARMA Graph Filters using Iterative Second-Order Cone Programming

Darukeesan Pakiyarajah, Chamira U. S. Edussooriya

We propose a weighted least-square (WLS) method to design autoregressive moving average (ARMA) graph filters. We first express the WLS design problem as a numerically-stable optimi…

eess.SP2021

A Novel Transfer Learning-Based Approach for Screening Pre-existing Heart Diseases Using Synchronized ECG Signals and Heart Sounds

Ramith Hettiarachchi, Udith Haputhanthri, Kithmini Herath +6

Diagnosing pre-existing heart diseases early in life is important as it helps prevent complications such as pulmonary hypertension, heart rhythm problems, blood clots, heart failur…

cs.CV2021★ 9 cited

Diverse Single Image Generation with Controllable Global Structure

Sutharsan Mahendren, Chamira Edussooriya, Ranga Rodrigo

Image generation from a single image using generative adversarial networks is quite interesting due to the realism of generated images. However, recent approaches need improvement…