@inproceedings{4c5be073391e4ac7b3e95445d8140376,
title = "Fixed-Point Implementation of Convolutional Neural Networks for Image Classification",
abstract = "In this paper, we show step-by-step how to design and optimize a fixed-point convolutional neural network (CNN) classifier. Moreover, the fixed-point classifier has been implemented using C++ programming and onto an FPGA. We show that the classifier with 4-bit fixed-point arithmetic with 8bit additions can classify handwritten digits with over 99.16% accuracy. Compared with the floating-point classifier which achieves 99.55% accuracy, the degradation due to fixed-point implementation is less than 0.4%.",
author = "Lo, {Chun Y.} and Lau, {Francis C.M.} and Sham, {Chiu Wing}",
year = "2018",
month = oct,
day = "18",
doi = "10.1109/ATC.2018.8587580",
language = "English",
series = "International Conference on Advanced Technologies for Communications",
publisher = "IEEE Computer Society",
pages = "105--109",
editor = "Bao, {Vo Nguyen Quoc} and Duy, {Tran Trung}",
booktitle = "Proceedings of 2018 International Conference on Advanced Technologies for Communications, ATC 2018",
address = "United States",
note = "11th International Conference on Advanced Technologies for Communications, ATC 2018 ; Conference date: 18-10-2018 Through 20-10-2018",
}