Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Azim Ahmadzadeh"'
Autor:
Azim Ahmadzadeh, Rohan Adhyapak, Kartik Chaurasiya, Laxmi Alekhya Nagubandi, V. Aparna, Petrus C. Martens, Alexei Pevtsov, Luca Bertello, Alexander Pevtsov, Naomi Douglas, Samuel McDonald, Apaar Bawa, Eugene Kang, Riley Wu, Dustin J. Kempton, Aya Abdelkarem, Patrick M. Copeland, Sri Harsha Seelamneni
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-15 (2024)
Abstract We present the Manually Annotated GONG Filaments in H-alpha Observations (MAGFiLO v1.0) dataset. This dataset contains 10,244 annotated filaments from 1,593 observations captured by the Global Oscillation Network Group (GONG), spanning the y
Externí odkaz:
https://doaj.org/article/13a69e292c4f40f0b27193c2e121b83f
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 45:1501-1513
In Machine Learning, a supervised model's performance is measured using the evaluation metrics. In this study, we first present our motivation by revisiting the major limitations of these metrics, namely one-dimensionality, lack of context, lack of i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::babe23ad3728c9069a440a5d9cb36c93
https://doi.org/10.1109/tpami.2022.3167007
https://doi.org/10.1109/tpami.2022.3167007
Publikováno v:
SoftwareX, Vol 12, Iss , Pp 100518- (2020)
We developed a domain-independent Python package to facilitate the preprocessing routines required in preparation of any multi-class, multivariate time series data. It provides a comprehensive set of 48 statistical features for extracting the importa
Externí odkaz:
https://doaj.org/article/dab28fbdd76a4ac49b5fff615e2c0866
Publikováno v:
Neural Computing and Applications. 34:13339-13353
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ecd856c6962386f13ad5796eda779f1
https://doi.org/10.1007/s00521-022-07361-8
https://doi.org/10.1007/s00521-022-07361-8
Publikováno v:
Artificial Intelligence and Soft Computing ISBN: 9783031234798
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1302bfae5b5dbaaacb51d39b75e791b8
https://doi.org/10.1007/978-3-031-23480-4_13
https://doi.org/10.1007/978-3-031-23480-4_13
Autor:
Rafal A. Angryk, Manolis K. Georgoulis, Azim Ahmadzadeh, Dustin Kempton, Yang Chen, Junzhi Wen
We report on progress made by our Data Mining Lab at Georgia State University on the interdisciplinary research project funded by the NSF-OAC-1931555 award. We take on two main challenges hindering data-driven solar flare forecasting, which are: (1)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::461498ef6bf8544b8fc9adc07f0b47bd
Autor:
Manolis K. Georgoulis, Sunitha Basodi, Sushant S. Mahajan, Dustin J. Kempton, Soukaina Filali Boubrahimi, Petrus C. Martens, Azim Ahmadzadeh, Rafal A. Angryk, Michael A. Schuh, Berkay Aydin, Xumin Cai, Shah Muhammad Hamdi
Publikováno v:
Scientific Data, Vol 7, Iss 1, Pp 1-13 (2020)
Scientific Data
Scientific Data
We introduce and make openly accessible a comprehensive, multivariate time series (MVTS) dataset extracted from solar photospheric vector magnetograms in Spaceweather HMI Active Region Patch (SHARP) series. Our dataset also includes a cross-checked N
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47eee827d64bc1e233c400a92845d882
http://link.springer.com/article/10.1038/s41597-020-0548-x
http://link.springer.com/article/10.1038/s41597-020-0548-x