4 citations · 8 across the 6 of their papers we have counts for
8 papers
ANTShapes Benchmarking Datasets for Event-Based Neuromorphic Object Classification
M. Middleton, H. Kayan, B. Sen Bhattacharya +7
Object classification in event-based computer vision is a task that is attracting considerable research attention. Event-based object classification is a fundamental task in the fi…
Modelling and Simulation of Neuromorphic Datasets for Anomaly Detection in Computer Vision
Mike Middleton, Teymoor Ali, Hakan Kayan +6
Limitations on the availability of Dynamic Vision Sensors (DVS) present a fundamental challenge to researchers of neuromorphic computer vision applications. In response, datasets h…
Assistive Chatbots for healthcare: a succinct review
Basabdatta Sen Bhattacharya, Vibhav Sinai Pissurlenkar
Artificial Intelligence (AI) for supporting healthcare services has never been more necessitated than by the recent global pandemic. Here, we review the state-of-the-art in AI-enab…
Sparse Distributed Memory using Spiking Neural Networks on Nengo
Rohan Deepak Ajwani, Arshika Lalan, Basabdatta Sen Bhattacharya +1
We present a Spiking Neural Network (SNN) based Sparse Distributed Memory (SDM) implemented on the Nengo framework. We have based our work on previous work by Furber et al, 2004, i…
Implementing a foveal-pit inspired filter in a Spiking Convolutional Neural Network: a preliminary study
Shriya T. P. Gupta, Basabdatta Sen Bhattacharya
We have presented a Spiking Convolutional Neural Network (SCNN) that incorporates retinal foveal-pit inspired Difference of Gaussian filters and rank-order encoding. The model is t…
Phase Entrainment by Periodic Stimuli In Silico: A Quantitative Study
Swapna Sasi, Basabdatta Sen Bhattacharya
We present a quantitative study of phase entrainment by periodic visual stimuli in a biologically inspired neural network. The objective is to understand the neuronal population dy…
Bayesian Optimisation for a Biologically Inspired Population Neural Network
Mahak Kothari, Swapna Sasi, Jun Chen +2
We have used Bayesian Optimisation (BO) to find hyper-parameters in an existing biologically plausible population neural network. The 8-dimensional optimal hyper-parameter combinat…
Quantifying Synchronization in a Biologically Inspired Neural Network
Pranav Mahajan, Advait Rane, Swapna Sasi +1
We present a collated set of algorithms to obtain objective measures of synchronisation in brain time-series data. The algorithms are implemented in MATLAB; we refer to our collate…