Zobrazeno 1 - 10
of 1 131
pro vyhledávání: '"spatial pyramid pooling"'
Autor:
Kumar, Akhil, Dhanalakshmi, R.
Publikováno v:
International Journal of Intelligent Computing and Cybernetics, 2024, Vol. 17, Issue 3, pp. 503-522.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJICC-02-2024-0077
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-20 (2024)
Abstract Background In complex agricultural environments, the presence of shadows, leaf debris, and uneven illumination can hinder the performance of leaf segmentation models for cucumber disease detection. This is further exacerbated by the imbalanc
Externí odkaz:
https://doaj.org/article/43b9834cc535474d9a51e1f9a59a4351
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract The precise delineation of urban aquatic features is of paramount importance in scrutinizing water resources, monitoring floods, and devising water management strategies. Addressing the challenge of indistinct boundaries and the erroneous cl
Externí odkaz:
https://doaj.org/article/57be98bf95c44913a0120d7ed19ae53f
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract The change detection (CD) technology has greatly improved the ability to interpret land surface changes. Deep learning (DL) methods have been widely used in the field of CD due to its high detection accuracy and application range. DL-based C
Externí odkaz:
https://doaj.org/article/d1db6f05f9b348e3a866ded55fe18d8a
Autor:
Huifeng Su, David Bonfils Kamanda, Tao Han, Cheng Guo, Rongzhao Li, Zhilei Liu, Fengzhao Su, Liuhong Shang
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract A bridge disease identification approach based on an enhanced YOLO v3 algorithm is suggested to increase the accuracy of apparent disease detection of concrete bridges under complex backgrounds. First, the YOLO v3 network structure is enhanc
Externí odkaz:
https://doaj.org/article/49ce76edf3ef4b729fb6602c80ec1e95
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 132, Iss , Pp 104025- (2024)
Inversion of the underwater temperature anomaly of mesoscale eddies from sea surface remote sensing data plays an important role in understanding the three-dimensional structure of eddies. In this article, a neural network structure, named the eddy t
Externí odkaz:
https://doaj.org/article/18f22c7b19924885acd7318da6104632
Publikováno v:
Heritage Science, Vol 12, Iss 1, Pp 1-15 (2024)
Abstract To address the fuzzy segmentation boundaries, missing details, small target losses and low efficiency of traditional segmentation methods in ancient mural image segmentation scenarios, this paper proposes a mural segmentation model based on
Externí odkaz:
https://doaj.org/article/bd67cb6cdf0947409c1deae1d14a1398
Publikováno v:
IEEE Access, Vol 12, Pp 116786-116800 (2024)
Speed bumps, as a crucial road safety infrastructure, can directly impact the accident rates on specific road sections if they have defects. Therefore, this study proposes a method for detecting speed bump multiclass defects using an improved YOLOv5s
Externí odkaz:
https://doaj.org/article/138c0fe8e8f24d19b5862df0b07b8f2f
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 12637-12648 (2024)
Deep learning (DL) algorithms are currently the most effective methods for change detection (CD) from high-resolution multispectral (MS) remote-sensing (RS) images. Because a variety of satellites are able to provide a lot of data, it is now easy to
Externí odkaz:
https://doaj.org/article/3486777c5a304ea2abb6491fd7c2998a
Publikováno v:
IEEE Access, Vol 12, Pp 32870-32880 (2024)
The detection of pavement diseases is an important and basic link in the road maintenance process. Many methods based on deep learning have been applied. However, these methods are not accurate enough and cannot accurately identify defects in complex
Externí odkaz:
https://doaj.org/article/9527c674c8fd49a496c5549dd30be290