activity
20132026
most citedEMNIST: an extension of MNIST to handwritten letters

464 citations · 495 across the 9 of their papers we have counts for

collaborators

15 papers

cs.SD2026

Towards Deployable Underwater Vessel Classification

Abishek Soti, Thura Pyae Sone, Naqib Ibnul +4

We propose a compact underwater acoustic classification framework combining multi-representation feature engineering, temporal statistical pooling, and compact convolutional archit…

eess.SP2026

Bio-inspired efficient cyclostationary analysis in machine and underwater acoustic recordings

Thura Pyae Sone, Abishek Soti, Henry Zhong +3

We propose a bio-inspired approach that uses the inner-hair-cell (IHC) response of the Cascade of Asymmetric Resonators with Fast-Acting Compression (CARFAC) model to efficiently e…

eess.AS2025

Real-time CARFAC Cochlea Model Acceleration on FPGA for Underwater Acoustic Sensing Systems

Bram Bremer, Matthew Bigelow, Stuart Anstee +3

This paper presents a real-time, energy-efficient embedded system implementing an array of Cascade of Asymmetric Resonators with Fast-Acting Compression (CARFAC) cochlea models for…

cs.CV2023

Density Invariant Contrast Maximization for Neuromorphic Earth Observations

Sami Arja, Alexandre Marcireau, Richard L. Balthazor +3

Contrast maximization (CMax) techniques are widely used in event-based vision systems to estimate the motion parameters of the camera and generate high-contrast images. However, th…

eess.SP2022★ 1 cited

Astrometric Calibration and Source Characterisation of the Latest Generation Neuromorphic Event-based Cameras for Space Imaging

Nicholas Owen Ralph, Alexandre Marcireau, Saeed Afshar +3

As an emerging approach to space situational awareness and space imaging, the practical use of an event-based camera in space imaging for precise source analysis is still in its in…

cs.NE2021★ 18 cited

An optimised deep spiking neural network architecture without gradients

Yeshwanth Bethi, Ying Xu, Gregory Cohen +2

We present an end-to-end trainable modular event-driven neural architecture that uses local synaptic and threshold adaptation rules to perform transformations between arbitrary spa…