Zobrazeno 1 - 10
of 196
pro vyhledávání: '"Roberto Togneri"'
Publikováno v:
Journal of Open Research Software, Vol 7, Iss 1 (2019)
We present DataDeps.jl: a julia package for the reproducible handling of static datasets to enhance the repeatability of scripts used in the data and computational sciences. It is used to automate the data setup part of running software which accompa
Externí odkaz:
https://doaj.org/article/5726aa25125d44e0b1f68e282e7753fe
Publikováno v:
Atmosphere, Vol 11, Iss 5, p 460 (2020)
A novel approach, using low Earth orbit (LEO) satellite microwave communication links for cloud liquid water measurements, is proposed in this paper. The feasibility of this approach is studied through simulations of the retrieval system including a
Externí odkaz:
https://doaj.org/article/9cf1fa2bbc5c4aa19a736487ae03f0e1
Publikováno v:
Cogent Engineering, Vol 3, Iss 1 (2016)
This paper presents the development of a new model reduction method for discrete-time bilinear systems based on the balanced truncation framework. In many model reduction applications, it is advantageous to analyze the characteristics of the system w
Externí odkaz:
https://doaj.org/article/36e3ab24dbb540b4920a68f188b37f39
Publikováno v:
Speech Communication. 147:22-40
Autor:
Siyu Sun, Jian Jin, Zhe Han, Xianjun Xia, Li Chen, Yijian Xiao, Piao Ding, Shenyi Song, Roberto Togneri, Haijian Zhang
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Autor:
Uzair Nadeem, Mohammed Bennamoun, Roberto Togneri, Ferdous Sohel, Aref Miri Rekavandi, Farid Boussaid
Publikováno v:
Pattern Recognition. 142:109655
Publikováno v:
Computational Linguistics and Intelligent Text Processing ISBN: 9783031238031
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c3353912c7fb569e11a58fe07446df9b
https://doi.org/10.1007/978-3-031-23804-8_1
https://doi.org/10.1007/978-3-031-23804-8_1
Publikováno v:
Circuits, Systems, and Signal Processing. 41:4068-4089
Spoofing attacks posed by generating artificial speech can severely degrade the performance of a speaker verification system. Recently, many anti-spoofing countermeasures have been proposed for detecting varying types of attacks from synthetic speech
Publikováno v:
IEEE Transactions on Information Forensics and Security. 17:280-291
Publikováno v:
Information Sciences. 580:578-597
This paper proposes a novel image set classification technique based on the concept of linear regression. Unlike most other approaches, the proposed technique does not require any training. We represent the gallery image sets as subspaces in a high d