Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Tuomas P. Oikarinen"'
Publikováno v:
IJCNN
The recent introduction of Graph Neural Networks (GNNs) and their growing popularity in the past few years has enabled the application of deep learning algorithms to non-Euclidean, graph-structured data. GNNs have achieved state-of-the-art results ac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::153271ffd127871ec08fe7953e308f7b
https://doi.org/10.1109/ijcnn52387.2021.9534301
https://doi.org/10.1109/ijcnn52387.2021.9534301
Autor:
Alessandro Sebastianelli, Stefania Sica, F. P iccirillo, M. S. Langenkamp, Tuomas P. Oikarinen, Silvia Liberata Ullo, M. P. DelRosso
Publikováno v:
IGARSS
In this paper, the authors aim to combine the latest state of the art models in image recognition with the best publicly available satellite images to create a system for landslide risk mitigation. We focus first on landslide detection and further pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e33eb13c63d8c22d5bf2959672ddfb36
https://doi.org/10.1109/igarss.2019.8898632
https://doi.org/10.1109/igarss.2019.8898632
Autor:
Julia B. Hyman, Adrian Fanucci-Kiss, Tuomas P. Oikarinen, Olivia Meisner, Robert Desimone, Guoping Feng, Rogier Landman, Karthik Srinivasan, Shivangi Parmar
This paper introduces an end-to-end feedforward convolutional neural network that is able to reliably classify the source and type of animal calls in a noisy environment using two streams of audio data after being trained on a dataset of modest size
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8752ae48a32fc0106e8403a35b5dba7f
https://europepmc.org/articles/PMC6786887/
https://europepmc.org/articles/PMC6786887/
Autor:
Guoping Feng, Tuomas P. Oikarinen, Karthik Srinivasan, Rogier Landman, Robert Desimone, Olivia Meisner, Julia B. Hyman, Shivangi Parmar
We introduce an end-to-end feedforward convolutional neural network that is able to reliably classify the source and type of animal calls in a noisy environment using two streams of audio data after being trained on a dataset of modest size and imper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d4e482f820d4b574d420ad68ef9164a
Autor:
Shivangi Parmar, Olivia Meisner, Adrian Fanucci-Kiss, Tuomas P. Oikarinen, Julia B. Hyman, Robert Desimone, Karthik Srinivasan, Rogier Landman, Guoping Feng
Publikováno v:
The Journal of the Acoustical Society of America. 145:2209-2209
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61f2d04d08c31e2b47f8f851e16477c7
https://doi.org/10.1121/1.5097583
https://doi.org/10.1121/1.5097583
Autor:
Mo, Kanghua1 (AUTHOR) mokanghua@gmail.com, Ye, Peigen2 (AUTHOR) ypgmhxy@gmail.com, Ren, Xiaojun1 (AUTHOR) renxiaojun@gzhu.edu.cn, Wang, Shaowei3 (AUTHOR) wangsw@gzhu.edu.cn, Li, Wenjun3 (AUTHOR) wenjun1999@e.gzhu.edu.cn, Li, Jin1 (AUTHOR) jinli71@gmail.com
Publikováno v:
ACM Computing Surveys. Jun2024, Vol. 56 Issue 6, p1-39. 39p.