@inproceedings{e69e0e60d6194c1e82729bd37100f4a6,
title = "Hardware/software co-design for a gender recognition embedded system",
abstract = "Gender recognition has applications in human-computer interaction, biometric authentication, and targeted marketing. This paper presents an implementation of an algorithm for binary male/female gender recognition from face images based on a shunting inhibitory convolutional neural network, which has a reported accuracy on the FERET database of 97.2 \%. The proposed hardware/software co-design approach using an ARM processor and FPGA can be used as an embedded system for a targeted marketing application to allow real-time processing. A threefold speedup is achieved in the presented approach compared to a software implementation on the ARM processor alone.",
keywords = "Co-design, Computer vision, Embedded system, FPGA, Hardware acceleration, Neural network, Real-time",
author = "Chen, \{Andrew Tzer Yeu\} and Morteza Biglari-Abhari and Wang, \{Kevin I.Kai\} and Abdesselam Bouzerdoum and Tivive, \{Fok Hing Chi\}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016 ; Conference date: 02-08-2016 Through 04-08-2016",
year = "2016",
doi = "10.1007/978-3-319-42007-3\_47",
language = "English",
isbn = "9783319420066",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "541--552",
editor = "Moonis Ali and Hamido Fujita and Jun Sasaki and Masaki Kurematsu and Ali Selamat",
booktitle = "Trends in Applied Knowledge-Based Systems and Data Science - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Proceedings",
address = "Germany",
}