1 code implementation • 9 Aug 2022 • Arvind Subramaniam, Aryan Mehra, Sayani Kundu
We tune BERT to perform this task in the form of rationales and class prediction, and compare our performance on different metrics spanning across accuracy, explainability and bias.
no code implementations • 7 Aug 2022 • Arvind Subramaniam
Throughout the span of this paper, we have emphasized on the employment of non-volatile memory devices such as memristors to realize artificial visual systems.
no code implementations • 7 Aug 2022 • Pavan Kumar Reddy Boppidi, Victor Jeffry Louis, Arvind Subramaniam, Rajesh K. Tripathy, Souri Banerjee, Souvik Kundu
The experimental results demonstrate that the proposed approach is very effective to separate image sources, and also the contrast of the images are improved with an improvement factor in terms of percentage of structural similarity as 67. 27% when compared with the software-based implementation of conventional ACY ICA and Fast ICA algorithms.
no code implementations • 7 Aug 2022 • Arvind Subramaniam, Avinash Sharma
Following a preliminary pruning step, N2NSkip connections are randomly added between individual neurons/channels of the pruned network, while maintaining the overall sparsity of the network.
no code implementations • 24 Nov 2020 • Swati Padhee, Amanuel Alambo, Tanvi Banerjee, Arvind Subramaniam, Daniel M. Abrams, Gary K. Nave Jr., Nirmish Shah
Our experimental results demonstrate that ML techniques can provide an objective and quantitative evaluation of pain intensity levels for all three types of hospital visits.