Zobrazeno 1 - 10
of 19 010
pro vyhledávání: '"convolutional neural network (cnn)."'
Publikováno v:
International Journal of Intelligent Computing and Cybernetics, 2024, Vol. 17, Issue 4, pp. 783-804.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJICC-04-2024-0189
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 1302-1316 (2025)
Single-image superresolution (SISR) of remote sensing images aims to improve image resolution through algorithmic means while restoring rich high-frequency detailed information. Previously, convolutional neural network (CNN) achieves impressive progr
Externí odkaz:
https://doaj.org/article/d309600927734128b923928f43ea4598
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 1007-1019 (2025)
Video synthetic aperture radar (SAR) has exhibited considerable potential for detecting and tracking ground moving targets. Numerous classical shadow-based detection methods have been applied in video SAR. In addition, shadow-assisted detection metho
Externí odkaz:
https://doaj.org/article/c3f0cd13ac784a8a88e007467f52ada0
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 1196-1211 (2025)
In hyperspectral image (HSI) classification, convolutional neural networks (CNNs) are widely used due to their ability to leverage the rich spectral information across multiple bands. However, HSI classification still faces various challenges, includ
Externí odkaz:
https://doaj.org/article/b644dd905935470cacc3ab699c3e9197
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 569-583 (2025)
The objective of super-resolution in remote sensing imagery is to enhance low-resolution images to recover high-quality details. With the rapid progress of deep learning technology, the deep learning-based super-resolution technology for remote sensi
Externí odkaz:
https://doaj.org/article/0f49c2987b8e4601bca4f0924b22efca
Publikováno v:
Journal of Rock Mechanics and Geotechnical Engineering, Vol 16, Iss 12, Pp 5061-5076 (2024)
The method for precursor information acquisition based on acoustic emission (AE) data for jointed rock masses is of significant importance for the early warning of dynamic disasters in underground engineering. A clustering-convolutional neural networ
Externí odkaz:
https://doaj.org/article/3dd9676e89ce4cbe97b749506472bbdd
Autor:
J.N.V.R. Swarup Kumar, I S Siva Rao, T M N Vamsi, T Ravi Kumar, K Rajendra Prasad, K Vijaya Kumar
Publikováno v:
Proceedings on Engineering Sciences, Vol 6, Iss 4, Pp 1751-1756 (2024)
Facial swapping technology is a rapidly growing area of research with a wide range of applications, including entertainment, security, and healthcare. In this project, a deep learning approach was used to achieve highly accurate and realistic face sw
Externí odkaz:
https://doaj.org/article/8e316d3c780c44e5b3f9dc8fb0356b95
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract This study aimed to develop a deep learning system for the detection of three-rooted mandibular first molars (MFMs) on panoramic radiographs and to assess its diagnostic performance. Panoramic radiographs, together with cone beam computed to
Externí odkaz:
https://doaj.org/article/1a3af7a8aed142db974b2a67728f7edd
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Tunnels in the Western Plateau region of China often face numerous problems of high ground stress, as well as highly fractured and weak rock masses in deep sections of the tunnel, which results in an increased risk of large soft rock deforma
Externí odkaz:
https://doaj.org/article/7c3795773e0640e2864cc8d42ae34fad
Probabilistic regression for autonomous terrain relative navigation via multi-modal feature learning
Autor:
Ickbum Kim, Sandeep Singh
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract The extension of human spaceflight across an ever-expanding domain, in conjunction with intricate mission architectures demands a paradigm shift in autonomous navigation algorithms, especially for the powered descent phase of planetary landi
Externí odkaz:
https://doaj.org/article/f37ff81a27854f69b46eef6dc84d8e31