@inproceedings{8468029bd0204390be3c173544266daa,
title = "High-speed image-free target detection and classification in single-pixel imaging",
abstract = "In this paper, an efficient image-free target detection and classification framework for single-pixel imaging (SPI) is presented. The proposed method captures target information by sampling it with very few patterns (at 1-10\% sampling rate), and employs signal-processing based feature extraction coupled with radial basis function neural network (RBF-NN) for accurate target classification. The proposed method can replace existing deep learning (DL) based target detection and classification methods because of its high-speed, accuracy and simple shallow design.",
keywords = "Deep learning, Radial basis function neural network, Single-pixel imaging, Target classification",
author = "Saad Rizvi and Jie Cao and Qun Hao",
note = "Publisher Copyright: Copyright {\textcopyright} 2020 SPIE.; SPIE Future Sensing Technologies 2020 ; Conference date: 09-11-2020 Through 13-11-2020",
year = "2020",
doi = "10.1117/12.2580557",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Masafumi Kimata and Shaw, \{Joseph A.\} and Valenta, \{Christopher R.\}",
booktitle = "SPIE Future Sensing Technologies",
address = "United States",
}