no code implementations • 28 Mar 2022 • Kithmini Herath, Udith Haputhanthri, Ramith Hettiarachchi, Hasindu Kariyawasam, Raja N. Ahmad, Azeem Ahmad, Balpreet S. Ahluwalia, Chamira U. S. Edussooriya, Dushan N. Wadduwage
Since the late 16th century, scientists have continuously innovated and developed new microscope types for various applications.
no code implementations • 23 May 2022 • Udith Haputhanthri, Kithmini Herath, Ramith Hettiarachchi, Hasindu Kariyawasam, Azeem Ahmad, Balpreet S. Ahluwalia, Chamira U. S. Edussooriya, Dushan N. Wadduwage
To this end, we present a learnable optical compression-decompression framework that learns content-specific features.
no code implementations • 27 Jun 2022 • Henry Arguello, Jorge Bacca, Hasindu Kariyawasam, Edwin Vargas, Miguel Marquez, Ramith Hettiarachchi, Hans Garcia, Kithmini Herath, Udith Haputhanthri, Balpreet Singh Ahluwalia, Peter So, Dushan N. Wadduwage, Chamira U. S. Edussooriya
The performance of COI systems highly depends on the design of its main components: the CE pattern and the computational method used to perform a given task.
no code implementations • 19 Oct 2022 • Navodini Wijethilake, Mithunjha Anandakumar, Cheng Zheng, Peter T. C. So, Murat Yildirim, Dushan N. Wadduwage
Limited throughput is a key challenge in in-vivo deep-tissue imaging using nonlinear optical microscopy.
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.
no code implementations • 13 Sep 2023 • Nirhoshan Sivaroopan, Chamuditha Jayanga, Chalani Ekanayake, Hasindri Watawana, Jathurshan Pradeepkumar, Mithunjha Anandakumar, Ranga Rodrigo, Chamira U. S. Edussooriya, Dushan N. Wadduwage
We show that our approach can reach the state-of-the-art (SOTA) for patch-level classification with only 1-10% randomly selected annotations compared to other SOTA approaches.
no code implementations • 21 Mar 2024 • Yasith Jayawardana, Azeem Ahmad, Balpreet S. Ahluwalia, Rafi Ahmad, Sampath Jayarathna, Dushan N. Wadduwage
Given a trained DNN and some input, we first feed the input through the DNN and compute an ensemble of OoD metrics, which we term latent responses.