Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Ranga Rodrigo"'
Autor:
Kavinda Kehelella, Gayangana Leelarathne, Dhanuka Marasinghe, Nisal Kariyawasam, Viduneth Ariyarathna, Arjuna Madanayake, Ranga Rodrigo, Chamira U. S. Edussooriya
Publikováno v:
IEEE Sensors Letters. 6:1-4
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::25a9dfed4d020e126f6c5cbaeb7b4479
https://doi.org/10.1109/lsens.2022.3206439
https://doi.org/10.1109/lsens.2022.3206439
Publikováno v:
Signal Processing: Image Communication. 110:116888
Light field saliency detection -- important due to utility in many vision tasks -- still lacks speed and can improve in accuracy. Due to the formulation of the saliency detection problem in light fields as a segmentation task or a memorizing task, ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6e3ff3072174b954f9319893cd4beb21
https://doi.org/10.1016/j.image.2022.116888
https://doi.org/10.1016/j.image.2022.116888
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 input data. However, most of the existing capsule based network approaches
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de8b4fc74568de9452ed8f202ad2d8d1
http://arxiv.org/abs/2112.11258
http://arxiv.org/abs/2112.11258
Autor:
Alex Xavier, Dumindu Tissera, Rukshan Wijesinghe, Kasun Vithanage, Ranga Rodrigo, Subha Fernando, Sanath Jayasena
Publikováno v:
2021 The 5th International Conference on Advances in Artificial Intelligence (ICAAI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92775195f54401775d2a4cfc4ee4b74e
https://doi.org/10.1145/3505711.3505715
https://doi.org/10.1145/3505711.3505715
Autor:
Dumindu Tissera, Rukshan Wijesinghe, Kasun Vithanage, Alex Xavier, Subha Fernando, Ranga Rodrigo
Neural networks are known to give better performance with increased depth due to their ability to learn more abstract features. Although the deepening of networks has been well established, there is still room for efficient feature extraction within
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f6c209900edbee396b3274c41688e74f
http://arxiv.org/abs/2107.02450
http://arxiv.org/abs/2107.02450
Autor:
Jathushan Rajasegaran, Sameera Ramasinghe, Vinoj Jayasundara, Ranga Rodrigo, Kanchana Ranasinghe, Ajith Pasqual
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 29:2693-2707
Activity recognition in videos in a deep-learning setting—or otherwise—uses both static and pre-computed motion components. The method of combining the two components, while keeping the burden on the deep network less, still remains uninvestigate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::08c5fc3c34108ff2260e69c535f64b0a
https://doi.org/10.1109/tcsvt.2017.2760858
https://doi.org/10.1109/tcsvt.2017.2760858
Autor:
Dumindu Tissera, Kasun Vithanage, Rukshan Wijesinghe, Alex Xavier, Sanath Jayasena, Subha Fernando, Ranga Rodrigo
Any clustering algorithm must synchronously learn to model the clusters and allocate data to those clusters in the absence of labels. Mixture model-based methods model clusters with pre-defined statistical distributions and allocate data to those clu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bbd1af6ff6a872bfe55873c263ee2a77
Autor:
Peshala Jayasekara, Ranga Rodrigo, Achintha Wijesinghe, Chinthani Kumaradasa, Naveen Karunanayake, Chameera Wijethunga
Publikováno v:
SMC
Reinforcement learning algorithms have been successfully trained for games like GO, Atari, and Chess in simulated environments. However, in cue sport-based games like Carrom, real world is unpredictable unlike in Chess and GO due to the stochastic na
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db323cb5a344cc78eb69922deae708ea
https://doi.org/10.1109/smc42975.2020.9283458
https://doi.org/10.1109/smc42975.2020.9283458
Autor:
Menusha Munasinghe, Hasitha Wellaboda, Adhitha Dias, Ranga Rodrigo, Peshala Jayasekara, Yasod Rasanka
Publikováno v:
2020 6th International Conference on Control, Automation and Robotics (ICCAR).
Getting a team of robots to achieve a relatively complex task using manual manipulation through augmented reality (AR) is interesting. However, the true potential of such an approach manifests when the system can learn from humans. We propose a syste
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::221af34b097d0c33fc28b43b2c396c82
https://doi.org/10.1109/iccar49639.2020.9108004
https://doi.org/10.1109/iccar49639.2020.9108004
Autor:
Ranga Rodrigo, Kumara Kahatapitiya, Rukshan Wijesinghe, Dumindu Tissera, Subha Fernando, Kasun Vithanage
Publikováno v:
ICPR
Learning a particular task from a dataset, samples in which originate from diverse contexts, is challenging, and usually addressed by deepening or widening standard neural networks. As opposed to conventional network widening, multi-path architecture
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c8304ae038c71a5401a1d0b45f75fed