Zobrazeno 1 - 10
of 134
pro vyhledávání: '"Sidike Paheding"'
Publikováno v:
IEEE Access, Vol 11, Pp 10412-10428 (2023)
The rise of vision-based environmental, marine, and oceanic exploration research highlights the need for supporting underwater image enhancement techniques to help mitigate water effects on images such as blurriness, low color contrast, and poor qual
Externí odkaz:
https://doaj.org/article/81d294170b6e47c0ab4f6ca9cfd228b1
Autor:
Yuchen Li, Jered Pawlak, Joshua Price, Khair Al Shamaileh, Quamar Niyaz, Sidike Paheding, Vijay Devabhaktuni
Publikováno v:
IEEE Access, Vol 10, Pp 16859-16870 (2022)
In this paper, a machine learning (ML) approach is proposed to detect and classify jamming attacks against orthogonal frequency division multiplexing (OFDM) receivers with applications to unmanned aerial vehicles (UAVs). Using software-defined radio
Externí odkaz:
https://doaj.org/article/09ba533f73c14e899f2fd66ec1fa75e0
Publikováno v:
IEEE Access, Vol 9, Pp 79534-79548 (2021)
Deep learning algorithms have seen acute growth of interest in their applications throughout several fields of interest in the last decade, with medical hyperspectral imaging being a particularly promising domain. So far, to the best of our knowledge
Externí odkaz:
https://doaj.org/article/f8d2d584ab3b49508762123fb22aa6e3
Publikováno v:
IEEE Access, Vol 9, Pp 82031-82057 (2021)
U-net is an image segmentation technique developed primarily for image segmentation tasks. These traits provide U-net with a high utility within the medical imaging community and have resulted in extensive adoption of U-net as the primary tool for se
Externí odkaz:
https://doaj.org/article/68db953783104b8383794d5a6c04dfd7
Publikováno v:
Applied Sciences, Vol 12, Iss 10, p 5159 (2022)
Deep learning (DL) algorithms have achieved significantly high performance in object detection tasks. At the same time, augmented reality (AR) techniques are transforming the ways that we work and connect with people. With the increasing popularity o
Externí odkaz:
https://doaj.org/article/b35596051cd244239202978ec8d3009a
Publikováno v:
in IEEE Access, vol. 9, pp. 79534-79548, 2021
Deep learning algorithms have seen acute growth of interest in their applications throughout several fields of interest in the last decade, with medical hyperspectral imaging being a particularly promising domain. So far, to the best of our knowledge
Externí odkaz:
http://arxiv.org/abs/2011.13974
U-net is an image segmentation technique developed primarily for medical image analysis that can precisely segment images using a scarce amount of training data. These traits provide U-net with a very high utility within the medical imaging community
Externí odkaz:
http://arxiv.org/abs/2011.01118
Autor:
Alom, Md Zahangir, Taha, Tarek M., Yakopcic, Christopher, Westberg, Stefan, Sidike, Paheding, Nasrin, Mst Shamima, Van Esesn, Brian C, Awwal, Abdul A S., Asari, Vijayan K.
Deep learning has demonstrated tremendous success in variety of application domains in the past few years. This new field of machine learning has been growing rapidly and applied in most of the application domains with some new modalities of applicat
Externí odkaz:
http://arxiv.org/abs/1803.01164
In spite of the advances in pattern recognition technology, Handwritten Bangla Character Recognition (HBCR) (such as alpha-numeric and special characters) remains largely unsolved due to the presence of many perplexing characters and excessive cursiv
Externí odkaz:
http://arxiv.org/abs/1705.02680
Autor:
Srinivasa Rao, P.C., Sravan Kumar, A.J., Niyaz, Quamar, Sidike, Paheding, Devabhaktuni, Vijay K
Publikováno v:
In Expert Systems With Applications 1 April 2021 167