MOSAIC: Masked Optimisation with Selective Attention for Image Reconstruction

no code implementations • 1 Jun 2023 • Pamuditha Somarathne, Tharindu Wickremasinghe, Amashi Niwarthana, A. Thieshanthan, Chamira U. S. Edussooriya, Dushan N. Wadduwage

To this end, we propose MOSAIC, a novel compressive sensing framework to reconstruct images given any random selection of measurements, sampled using a fixed basis.

Compressive Sensing Image Reconstruction

HPGNN: Using Hierarchical Graph Neural Networks for Outdoor Point Cloud Processing

no code implementations • 5 Jun 2022 • Arulmolivarman Thieshanthan, Amashi Niwarthana, Pamuditha Somarathne, Tharindu Wickremasinghe, Ranga Rodrigo

Inspired by recent improvements in point cloud processing for autonomous navigation, we focus on using hierarchical graph neural networks for processing and feature learning over large-scale outdoor LiDAR point clouds.

Autonomous Navigation Graph Neural Network +1

Towards Real-time Traffic Sign and Traffic Light Detection on Embedded Systems

1 code implementation • 5 May 2022 • Oshada Jayasinghe, Sahan Hemachandra, Damith Anhettigama, Shenali Kariyawasam, Tharindu Wickremasinghe, Chalani Ekanayake, Ranga Rodrigo, Peshala Jayasekara

In this work, we propose a simple deep learning based end-to-end detection framework, which effectively tackles challenges inherent to traffic sign and traffic light detection such as small size, large number of classes and complex road scenarios.