Deep Spiking Neural Network for Energy-Efficient SAR Ship Detection

Minjung Yoo; Jungong Han; Sunok Kim

doi:10.1109/lgrs.2025.3549108

ScienceGate Book Chapters

JOURNAL ARTICLE

Deep Spiking Neural Network for Energy-Efficient SAR Ship Detection

Minjung Yoo Jungong Han Sunok Kim

Year: 2025 Journal: IEEE Geoscience and Remote Sensing Letters Vol: 22 Pages: 1-5 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/lgrs.2025.3549108

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Synthetic aperture radar Spiking neural network Artificial neural network Artificial intelligence Energy (signal processing) Remote sensing Geology

Metrics

Cited By

9.38

FWCI (Field Weighted Citation Impact)

Refs

0.84

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Underwater Acoustics Research

Physical Sciences → Earth and Planetary Sciences → Oceanography

Advanced SAR Imaging Techniques

Physical Sciences → Engineering → Aerospace Engineering

Synthetic Aperture Radar (SAR) Applications and Techniques

Physical Sciences → Engineering → Aerospace Engineering

Deep Spiking Neural Network for Energy-Efficient SAR Ship Detection

Metrics

Citation History

Topics

Related Documents

Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detection

Energy-Efficient Attention-Based Spiking YOLO Network for SAR Ship Detection

Spiking-NeRF: Spiking Neural Network for Energy-Efficient Neural Rendering

Neuromorphic Energy Efficient Stress Detection System using Spiking Neural Network

Energy-efficient EEG-based epileptic seizure detection: A deep learning-based spiking neural network approach