Search Results for author: Arvind Subramaniam

Found 5 papers, 1 papers with code

Exploring Hate Speech Detection with HateXplain and BERT

1 code implementation9 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.

Hate Speech Detection

Implementation of fast ICA using memristor crossbar arrays for blind image source separations

no code implementations7 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.

blind source separation

N2NSkip: Learning Highly Sparse Networks using Neuron-to-Neuron Skip Connections

no code implementations7 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.

Network Pruning

A neuromorphic approach to image processing and machine vision

no code implementations7 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.

Image Segmentation Object Recognition +1

Pain Intensity Assessment in Sickle Cell Disease patients using Vital Signs during Hospital Visits

no code implementations24 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.

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