@inproceedings{816f9ea19de74054bb424d1fba948307,
title = "FMRI visual image reconstruction using sparse logistic regression with a tunable regularization parameter",
abstract = "fMRI has been a popular way for encoding and decoding human visual cortex activity. A previous research reconstructed binary image using a sparse logistic regression (SLR) with fMRI activity patterns as its input. In this article, based on SLR, we propose a new sparse logistic regression with a tunable regularization parameter (SLR-T), which includes the SLR and maximum likelihood regression (MLR) as two special cases. By choosing a proper regularization parameter in SLR-T, it may yield a better performance than both SLR and MLR. An fMRI visual image reconstruction experiment is carried out to verify the performance of SLR-T.",
keywords = "FMRI, Sparse regression, Visual image reconstruction",
author = "Hao Wu and Jiayi Wang and Badong Chen and Nanning Zheng",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015 ; Conference date: 28-10-2015 Through 30-10-2015",
year = "2015",
doi = "10.1007/978-3-319-25159-2\_77",
language = "英语",
isbn = "9783319251585",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "825--830",
editor = "Zili Zhang and Songmao Zhang and Zili Zhang and Martin Wirsing and Martin Wirsing and Martin Wirsing and Zili Zhang and Songmao Zhang and Songmao Zhang",
booktitle = "Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings",
}