activity
20172024
most citedDigital Signal Processing Using Deep Neural Networks

3 citations · 4 across the 5 of their papers we have counts for

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Showing cs.CVShow all

5 papers · 1 filter

cs.CV2024

Event-to-Video Conversion for Overhead Object Detection

Darryl Hannan, Ragib Arnab, Gavin Parpart +3

Collecting overhead imagery using an event camera is desirable due to the energy efficiency of the image sensor compared to standard cameras. However, event cameras complicate down…

cs.CV2023

Implementing and Benchmarking the Locally Competitive Algorithm on the Loihi 2 Neuromorphic Processor

Gavin Parpart, Sumedh R. Risbud, Garrett T. Kenyon +1

Neuromorphic processors have garnered considerable interest in recent years for their potential in energy-efficient and high-speed computing. The Locally Competitive Algorithm (LCA…

cs.CV2023★ 1 cited

ColMix -- A Simple Data Augmentation Framework to Improve Object Detector Performance and Robustness in Aerial Images

Cuong Ly, Grayson Jorgenson, Dan Rosa de Jesus +3

In the last decade, Convolutional Neural Network (CNN) and transformer based object detectors have achieved high performance on a large variety of datasets. Though the majority of…

cs.CV2022

Dictionary Learning with Accumulator Neurons

Gavin Parpart, Carlos Gonzalez, Terrence C. Stewart +6

The Locally Competitive Algorithm (LCA) uses local competition between non-spiking leaky integrator neurons to infer sparse representations, allowing for potentially real-time exec…

cs.CV2017

Image Compression: Sparse Coding vs. Bottleneck Autoencoders

Yijing Watkins, Mohammad Sayeh, Oleksandr Iaroshenko +1

Bottleneck autoencoders have been actively researched as a solution to image compression tasks. However, we observed that bottleneck autoencoders produce subjectively low quality r…