All adder neural networks for on-board remote sensing scene classification

N Zhang, G Wang, J Wang, H Chen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Directly performing remote sensing scene classification (RSSC) on satellites can effectively
relieve pressures on data downlinks. However, existing convolutional neural network (CNN) …

Solving a steady-state PDE using spiking networks and neuromorphic hardware

JD Smith, W Severa, AJ Hill, L Reeder… - International …, 2020 - dl.acm.org
The widely parallel, spiking neural networks of neuromorphic processors can enable
computationally powerful formulations. While recent interest has focused on primarily …

Co-design of free-space metasurface optical neuromorphic classifiers for high performance

F Léonard, AS Backer, EJ Fuller, C Teeter… - ACS …, 2021 - ACS Publications
Classification of features in a scene typically requires conversion of the incoming photonic
field into the electronic domain. Recently, an alternative approach has emerged whereby …

A Lightweight Patch-Level Change Detection Network Based on Multi-layer Feature Compression and Sensitivity-Guided Network Pruning

L Xue, X Wang, Z Wang, G Li, H Song… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Existing satellite remote sensing change detection (CD) methods often crop large-scale
bitemporal image pairs into small patch pairs and then use pixel-level CD methods for fair …

An Extremely Pipelined FPGA-based accelerator of All Adder Neural Networks for On-board Remote Sensing Scene Classification

N Zhang, S Ni, T Qiao, W Liu… - … Conference on Field …, 2023 - ieeexplore.ieee.org
Directly completing remote sensing scene classification (RSSC) on space platforms can
minimize latency and relieve data downlink burdens. The all adder neural network (A^2 NN) …

Enhancing Remote Sensing Image Scene Classification with Satellite-Terrestrial Collaboration and Attention-Aware Transmission Policy

A Lu, Y Hu, Z Cao, J Liu, L Li, Z Li - IEEE Transactions on …, 2025 - ieeexplore.ieee.org
Advancements in Earth observation sensors on low Earth orbit (LEO) satellites have
significantly increased the volume of remote sensing images. This growth has led to …

Deep Reinforcement Learning Methods for Discovering Novel Neuromorphic Devices

DC Crowder, JD Smith, SG Cardwell - Proceedings of the 2023 …, 2023 - dl.acm.org
Innovation in the field of neuromorphic computing is characterized by long periods of slow,
steady growth that are punctuated by periods of rapid discovery. In order to accelerate …

An introduction to neuromorphic computing and its potential impact for unattended ground sensors

AJ Hill, CM Vineyard - 2021 - osti.gov
Neuromorphic computers are hardware systems that mimic the brain's computational
process phenomenology. This is in contrast to neural network accelerators, such as the …