Cloudsatnet-1: Fpga-based hardware-accelerated quantized cnn for satellite on-board cloud coverage classification
CubeSats, the nanosatellites and microsatellites with a wet mass up to 60 kg, accompanied
by the cost decrease of accessing the space, amplified the rapid development of the Earth …
by the cost decrease of accessing the space, amplified the rapid development of the Earth …
Investigating spiking neural networks for energy-efficient on-board ai applications. a case study in land cover and land use classification
Spiking neural networks have been attracting the interest of researchers due to their
potential energy efficiency. This feature makes them appealing for applications on board …
potential energy efficiency. This feature makes them appealing for applications on board …
FPGA-based CNN for real-time UAV tracking and detection
Neural networks (NNs) are now being extensively utilized in various artificial intelligence
platforms specifically in the area of image classification and real-time object tracking. We …
platforms specifically in the area of image classification and real-time object tracking. We …
A methodology to design quantized deep neural networks for automatic modulation recognition
Next-generation communication systems will face new challenges related to efficiently
managing the available resources, such as the radio spectrum. DL is one of the optimization …
managing the available resources, such as the radio spectrum. DL is one of the optimization …
Machine Learning in Space: Surveying the Robustness of on-board ML models to Radiation
K Lange, F Fontana, F Rossi, M Varile… - arXiv preprint arXiv …, 2024 - arxiv.org
Modern spacecraft are increasingly relying on machine learning (ML). However, physical
equipment in space is subject to various natural hazards, such as radiation, which may …
equipment in space is subject to various natural hazards, such as radiation, which may …
Pattern Classification Using Quantized Neural Networks for FPGA-Based Low-Power IoT Devices
With the recent growth of the Internet of Things (IoT) and the demand for faster computation,
quantized neural networks (QNNs) or QNN-enabled IoT can offer better performance than …
quantized neural networks (QNNs) or QNN-enabled IoT can offer better performance than …
Profiling Power Consumption for Deep Learning on Resource Limited Devices
A Duggan, T Scully, N Smith, A Giltinan - International Conference on …, 2023 - Springer
The introduction of convolutional neural networks (CNN) has had a significant impact on
various computer vision tasks. The process of inference, where a CNN takes images as …
various computer vision tasks. The process of inference, where a CNN takes images as …
[PDF][PDF] Neural Network Compression for On Board Space Payloads
P Barmpakos - 2021 - ikee.lib.auth.gr
Abstract Space missions and flight vehicles up to date are constantly enhancing their system
and instrument capabilities, feeding the domain with new and more complex data. However …
and instrument capabilities, feeding the domain with new and more complex data. However …