no code implementations • 26 Dec 2023 • Peng Kang, Srutarshi Banerjee, Henry Chopp, Aggelos Katsaggelos, Oliver Cossairt
Recent advances in event-based shape determination from polarization offer a transformative approach that tackles the trade-off between speed and accuracy in capturing surface geometries.
no code implementations • 4 Nov 2023 • Srutarshi Banerjee, Miesher Rodrigues, Manuel Ballester, Alexander H. Vija, Aggelos K. Katsaggelos
Our novel approach is the first to characterize a full 3D charge transport model of the RTSD.
1 code implementation • 9 Oct 2022 • Peng Kang, Srutarshi Banerjee, Henry Chopp, Aggelos Katsaggelos, Oliver Cossairt
Moreover, to demonstrate the representation effectiveness of our proposed neurons and capture the complex spatio-temporal dependencies in the event-driven tactile data, we exploit the location spiking neurons to propose two hybrid models for event-driven tactile learning.
1 code implementation • 23 Jul 2022 • Peng Kang, Srutarshi Banerjee, Henry Chopp, Aggelos Katsaggelos, Oliver Cossairt
In this paper, to improve the representative capabilities of existing spiking neurons, we propose a novel neuron model called "location spiking neuron", which enables us to extract features of event-based data in a novel way.
no code implementations • 29 May 2021 • Srutarshi Banerjee, Henry H. Chopp, Jianping Zhang, Zihao W. Wang, Oliver Cossairt, Aggelos Katsaggelos
The detection and tracking of objects in the scene are done on the distorted data at the host.
no code implementations • 12 May 2021 • Henry H. Chopp, Srutarshi Banerjee, Oliver Cossairt, Aggelos K. Katsaggelos
In this paper, we propose EveRestNet, a convolutional neural network designed to remove blocking artifacts in videostreams using events from neuromorphic sensors.
no code implementations • 3 May 2020 • Srutarshi Banerjee, Zihao W. Wang, Henry H. Chopp, Oliver Cossairt, Aggelos Katsaggelos
The histograms are then variably sampled via Poisson Disk Sampling prioritized by the QT based segmentation map.