Application of Object Detection Approaches on the Wideband Sensing Problem
Author:
Affiliation:
1. Informatics and Information Security Research Center (BİLGEM), TÜBİTAK,Kocaeli,Turkey
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9858123/9858124/09858132.pdf?arnumber=9858132
Reference22 articles.
1. A Downscaled Faster-RCNN Framework for Signal Detection and Time-Frequency Localization in Wideband RF Systems
2. Joint Detection and Classification of RF Signals Using Deep Learning
3. Labeling of Radio Signal by Jointly Using Feature Engineering and Unsupervised Learning
4. Wideband spectral monitoring using deep learning
5. Spectrum Sensing and Signal Identification With Deep Learning Based on Spectral Correlation Function
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3. Stitching the Spectrum: Semantic Spectrum Segmentation with Wideband Signal Stitching;IEEE INFOCOM 2024 - IEEE Conference on Computer Communications;2024-05-20
4. An Optimized Faster Region-Based CNN for 1D Spectrum Sensing and Signal Identification in Cluttered RF Environments;2023 IEEE Future Networks World Forum (FNWF);2023-11-13
5. CCD-GAN for Domain Adaptation in Time-Frequency Localization-Based Wideband Spectrum Sensing;IEEE Communications Letters;2023-09
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