no code implementations • 17 Sep 2023 • Anton Jeran Ratnarajah, Sahani Goonetilleke, Dumindu Tissera, Kapilan Balagopalan, Ranga Rodrigo
Video synopsis, summarizing a video to generate a shorter video by exploiting the spatial and temporal redundancies, is important for surveillance and archiving.
no code implementations • 17 Sep 2023 • Anton Jeran Ratnarajah, Sahani Goonetilleke, Dumindu Tissera, Kapilan Balagopalan, Ranga Rodrigo
This project has resulted in three research outcomes Moving Object Based Collision Free Video Synopsis, Forensic and Surveillance Analytic Tool Architecture and Tampering Detection Inter-Frame Forgery.
no code implementations • 29 Sep 2021 • Mihira Kasun Vithanage, Rukshan Darshana Wijesinghe, Alex Xavier, Dumindu Tissera, Sanath Jayasena, Subha Fernando
In this paper, we present a learning environment where agents are pressured to make their emerging languages compositional by incorporating a metric of topological similarity into the loss function.
no code implementations • 6 Jul 2021 • Dumindu Tissera, Rukshan Wijessinghe, Kasun Vithanage, Alex Xavier, Subha Fernando, Ranga Rodrigo
Having multiple parallel convolutional/dense operations in each layer solves this problem, but without any context-dependent allocation of resources among these operations: the parallel computations tend to learn similar features making the widening process less effective.
no code implementations • 6 Jul 2021 • Dumindu Tissera, Kasun Vithanage, Rukshan Wijesinghe, Alex Xavier, Sanath Jayasena, Subha Fernando, Ranga Rodrigo
The network parameters pose as the parameters of those distributions.
no code implementations • 16 Feb 2021 • Rukshan Wijesinghe, Kasun Vithanage, Dumindu Tissera, Alex Xavier, Subha Fernando, Jayathu Samarawickrama
Recent advances in Reinforcement Learning (RL) have surpassed human-level performance in many simulated environments.
no code implementations • 25 Jun 2020 • Nadarasar Bahavan, Navaratnarajah Suman, Sulhi Cader, Ruwinda Ranganayake, Damitha Seneviratne, Vinu Maddumage, Gershom Seneviratne, Yasinha Supun, Isuru Wijesiri, Suchitha Dehigaspitiya, Dumindu Tissera, Chamira Edussooriya
In the competition dataset of camera frames consisting of both normal and anomalous cases, we achieve a test accuracy of 94% and an F1-score of 0. 95.
no code implementations • 24 Jun 2020 • Dumindu Tissera, Kasun Vithanage, Rukshan Wijesinghe, Kumara Kahatapitiya, Subha Fernando, Ranga Rodrigo
As opposed to conventional network widening, multi-path architectures restrict the quadratic increment of complexity to a linear scale.
no code implementations • 26 Jul 2019 • Dumindu Tissera, Kumara Kahatapitiya, Rukshan Wijesinghe, Subha Fernando, Ranga Rodrigo
In view of this, networks which can allocate resources according to the context of the input and regulate flow of information across the network are effective.
Ranked #2 on Image Classification on Kuzushiji-MNIST
1 code implementation • 7 May 2019 • Kumara Kahatapitiya, Dumindu Tissera, Ranga Rodrigo
Occlusion removal is an interesting application of image enhancement, for which, existing work suggests manually-annotated or domain-specific occlusion removal.