Zobrazeno 1 - 10
of 183
pro vyhledávání: '"Ghaderpour, Ebrahim"'
Autor:
Xu Pengru, Zhou Junhui, Kausar Nasreen, Lin Chunlei, Lu Qianqian, Ghaderpour Ebrahim, Pamucar Dragan, Zadeh Ardashir M.
Publikováno v:
Demonstratio Mathematica, Vol 57, Iss 1, Pp 339-350 (2024)
Wearable sensors (WS) play a vital role in health assistance to improve the patient monitoring process. However, the existing data collection process faces difficulties in error corrections, rehabilitation, and training validations. Therefore, the da
Externí odkaz:
https://doaj.org/article/62d48a41305b4b29b4bd3c848ffee115
Autor:
Aliabad, Fahime Arabi, Zare, Mohammad, Malamiri, Hamidreza Ghafarian, Pouriyeh, Amanehalsadat, Shahabi, Himan, Ghaderpour, Ebrahim, Mazzanti, Paolo
Publikováno v:
In Ecological Informatics November 2024 83
Publikováno v:
In Heliyon 15 October 2024 10(19)
Publikováno v:
In Signal Processing October 2024 223
Publikováno v:
Sensors 2022, 22(6), 2346
Emotion recognition using EEG has been widely studied to address the challenges associated with affective computing. Using manual feature extraction methods on EEG signals results in sub-optimal performance by the learning models. With the advancemen
Externí odkaz:
http://arxiv.org/abs/2201.12055
Publikováno v:
Sensors 2022, 22, 2948
Electroencephalogram (EEG) signals may get easily contaminated by muscle artifacts, which may lead to wrong interpretation in the brain--computer interface (BCI) system as well as in various medical diagnoses. The main objective of this paper is to r
Externí odkaz:
http://arxiv.org/abs/2201.01462
Autor:
Ghaderpour, Ebrahim1,2 (AUTHOR) claudia.masciulli@uniroma1.it, Masciulli, Claudia1,2 (AUTHOR) marta.zocchi@uniroma1.it, Zocchi, Marta1 (AUTHOR) francesca.bozzano@uniroma1.it, Bozzano, Francesca1,2 (AUTHOR) gabriele.scarasciamugnozza@uniroma1.it, Scarascia Mugnozza, Gabriele1,2 (AUTHOR) paolo.mazzanti@uniroma1.it, Mazzanti, Paolo1,2 (AUTHOR)
Publikováno v:
Remote Sensing. Aug2024, Vol. 16 Issue 16, p3055. 22p.
Autor:
Yan, Shu-Rong, Dai, Ying, Shakibjoo, Ali Dokht, Zhu, Lixing, Taghizadeh, Sima, Ghaderpour, Ebrahim, Mohammadzadeh, Ardashir
Publikováno v:
In Energy Reports December 2024 12:187-196
Publikováno v:
Sensors 2021, 21(23), 8083
Efficiently implementing remote sensing image classification with high spatial resolution imagery can provide a significant value in Land Use and Land Cover (LULC) classification. The new advances in remote sensing and deep learning technologies have
Externí odkaz:
http://arxiv.org/abs/2110.02580
Publikováno v:
In Heliyon 15 July 2024 10(13)