Investigating the resolution-performance trade-off of object detection models in support of the Sustainable Development Goals

CN Clark, A Bedada, B Huff, B Lita… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Satellite imagery provides impartial, inclusive, and timely geospatial data regarding global
issues, supplementing traditional ground-based methods. The volume, velocity, and variety …

Scaling Deep Learning Research with Kubernetes on the NRP Nautilus HyperCluster

JA Hurt, A Ouadou, M Alshehri, GJ Scott - arXiv preprint arXiv:2411.12038, 2024 - arxiv.org
Throughout the scientific computing space, deep learning algorithms have shown excellent
performance in a wide range of applications. As these deep neural networks (DNNs) …

Analysis of deep learning techniques for maasai boma mapping in tanzania

K Cheng, I Popescu, L Sheets… - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
Underdeveloped countries in sub-Saharan Africa often contain cultural subpopulations that
are underserved in regard to health and education. This perpetuates the health challenges …

Automatic maasailand boma mapping with deep neural networks

K Cheng, IM Popescu, L Sheets… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
A prevalent challenge in underdeveloped countries is the mapping and accounting of
certain sub-populations for public health matters. This is especially true in sub-Saharan …

Neural Network Guided Variability Detection in Geospatial Data

AM Salama - 2023 - search.proquest.com
Geospatial data refers to data associated with a specific location on the earth's surface. It
plays an important role in a wide range of applications, including environmental monitoring …