Zobrazeno 1 - 10
of 1 756
pro vyhledávání: '"modal data"'
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 1786-1795 (2024)
The rapid growth of spatially resolved transcriptomics technology provides new perspectives on spatial tissue architecture. Deep learning has been widely applied to derive useful representations for spatial transcriptome analysis. However, effectivel
Externí odkaz:
https://doaj.org/article/38c75f58ae0645099f30bf3164b7bed4
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 135, Iss , Pp 104241- (2024)
The heterogeneity and complexity of multimodal data in high-resolution remote sensing images significantly challenges existing cross-modal networks in fusing the complementary information of high-resolution optical and synthetic aperture radar (SAR)
Externí odkaz:
https://doaj.org/article/4d1acf6a071f44018b48ac968220ba00
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
ABSTRACTThe urban environment exhibits significant vertical variations, Light Detection and Ranging (LiDAR) point cloud classification can provide insights for the 3D morphology of the urban environment. Introducing the adjacency relationships betwee
Externí odkaz:
https://doaj.org/article/3973ad9126bc49688dbe11b969d7a6e3
Publikováno v:
Heliyon, Vol 10, Iss 22, Pp e40351- (2024)
Variational Mode Decomposition (VMD) is extensively utilized in the domain of rotating machinery fault diagnosis. Nevertheless, the reliance on empirical parameter tuning and the limitations inherent in traditional single-signal (either vibration sig
Externí odkaz:
https://doaj.org/article/d6f70159a6ca4af0bf14804b2b354cdc
Publikováno v:
In Heliyon 30 November 2024 10(22)
Autor:
Yi, Sanli ⁎, Feng, Xueli
Publikováno v:
In Computers and Electrical Engineering April 2025 123 Part A
Publikováno v:
Mathematical Biosciences and Engineering, Vol 21, Iss 4, Pp 4989-5006 (2024)
Due to irregular sampling or device failure, the data collected from sensor network has missing value, that is, missing time-series data occurs. To address this issue, many methods have been proposed to impute random or non-random missing data. Howev
Externí odkaz:
https://doaj.org/article/d4bd62fec1864f429ea1498affcca648
Autor:
Minggang Liu, Xiaoxu Hu
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
Introduction: In the context of the evolving energy landscape, the efficient integration of energy storage systems (ESS) has become essential for optimizing power system operation and accommodating renewable energy sources.Methods: This study introdu
Externí odkaz:
https://doaj.org/article/5ff8bce4cb944562ab5621a0d2f3952c
Autor:
Ning Zhang, Wenqing Zhu
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
The disparity between human and machine perception of spatial information presents a challenge for machines to accurately sense their surroundings and improve target detection performance. Cross-modal data fusion emerges as a potential solution to en
Externí odkaz:
https://doaj.org/article/76e1430ffc3a4334a1000451da6b5717
Publikováno v:
PeerJ Computer Science, Vol 10, p e1993 (2024)
Non-linear dimensionality reduction can be performed by manifold learning approaches, such as stochastic neighbour embedding (SNE), locally linear embedding (LLE) and isometric feature mapping (ISOMAP). These methods aim to produce two or three laten
Externí odkaz:
https://doaj.org/article/dcb5b13dca3c41cc8e876a2c69e161b2