Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Watcharapan Suwansantisuk"'
Publikováno v:
IEEE Access, Vol 12, Pp 138061-138075 (2024)
Generalized frequency-division multiplexing (GFDM) is a potential multicarrier scheme for the fifth-generation wireless communication and beyond owing to its advantages over orthogonal frequency-division multiplexing (OFDM). Despite its benefits, GFD
Externí odkaz:
https://doaj.org/article/8c328a87aeb0468aaeb2857d9ed4abfa
Publikováno v:
IEEE Access, Vol 12, Pp 61359-61374 (2024)
Generalized frequency division multiplexing (GFDM) is a waveform for the next-generation communication but requires a step dedicated to time and frequency synchronization. The current time and frequency synchronization methods of GFDM do not fully ad
Externí odkaz:
https://doaj.org/article/bf5b75462d044c34ae98dd68c506b58e
Publikováno v:
IEEE Access, Vol 10, Pp 33421-33439 (2022)
Several computationally intensive applications in machine learning, signal processing, and computer vision call for convolution between a fixed vector and each of the incoming vectors. Often, the convolution need not be exact because a subsequent pro
Externí odkaz:
https://doaj.org/article/3affc1a47cf94bb0a332d4167bd9bcb8
Publikováno v:
IEEE Access, Vol 8, Pp 22048-22071 (2020)
Supervised learning has tremendous applications in cancer prediction, patient treatment, business, and engineering. Datasets for supervised learning are often corrupted by noise and non-biological effects, leading to model-overfitting and performance
Externí odkaz:
https://doaj.org/article/0b0a919a0b7c45d99df2e4d271574a6d
Publikováno v:
International Journal of Electrical & Computer Engineering (2088-8708); Apr2024, Vol. 14 Issue 2, p2344-2360, 17p
Publikováno v:
IEEE Access, Vol 8, Pp 22048-22071 (2020)
Supervised learning has tremendous applications in cancer prediction, patient treatment, business, and engineering. Datasets for supervised learning are often corrupted by noise and non-biological effects, leading to model-overfitting and performance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::878dc2d5f76bdb8f0f9ed5ab1b48ec45
https://ieeexplore.ieee.org/document/8963690/
https://ieeexplore.ieee.org/document/8963690/
Publikováno v:
2021 9th International Electrical Engineering Congress (iEECON).
Partial face recognition from videos has practical applications to surveillance and threats monitoring, but is difficult to perform accurately due to an absence of facial information and due to environmental effects, such as a poor resolution, noise,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c131e87893601615b8e4fa8a8afcbc10
https://doi.org/10.1109/ieecon51072.2021.9440364
https://doi.org/10.1109/ieecon51072.2021.9440364
Autor:
Watcharapan Suwansantisuk, Krissada Suchatpattmakul, Watcharakorn Buttijak, Surakarn Suksirisophak
Publikováno v:
SICE
Binary classification has applications in several areas, including the Internet of Things (IoT), and can be achieved by learning a predictive model from a labelled training dataset. A training dataset that is imbalanced leads undesirably to an inaccu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2655a55510de640fba4df32f7290ba8a
https://doi.org/10.23919/sice48898.2020.9240403
https://doi.org/10.23919/sice48898.2020.9240403
Publikováno v:
SICE
Generalized frequency division multiplexing (GFDM) is a major candidate for the fifth-generation (5G) waveform and beyond, and can be used as a modulation technique for Internet of things (IoT) applications. GFDM, however, requires dedicated step to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e8f0367f14af405d7a43707f5a32eb1
https://doi.org/10.23919/sice48898.2020.9240414
https://doi.org/10.23919/sice48898.2020.9240414
Publikováno v:
2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON).
Face recognition is a fundamental task that enables advanced applications in video surveillance, human-computer interaction, and security. Existing methods of face recognition do not perform well on non-frontal faces, which often come from multiple s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8302e63cf4cd0fee23afe9e47b47f7c3
https://doi.org/10.1109/ecti-con49241.2020.9158102
https://doi.org/10.1109/ecti-con49241.2020.9158102