Zobrazeno 1 - 10
of 341
pro vyhledávání: '"Implicit neural representation"'
Publikováno v:
Photoacoustics, Vol 39, Iss , Pp 100641- (2024)
Multispectral photoacoustic tomography (PAT) is an imaging modality that utilizes the photoacoustic effect to achieve non-invasive and high-contrast imaging of internal tissues but also molecular functional information derived from multi-spectral mea
Externí odkaz:
https://doaj.org/article/831b017a09924e89b48c22777f2c36af
Publikováno v:
Materials & Design, Vol 249, Iss , Pp 113529- (2025)
Lightweight structures are ubiquitous in nature and extensively applied in high-end industries for load-bearing purpose. Parametric design is superior for its rapid generation of complex geometries controlled by user-specified parameters, thus has be
Externí odkaz:
https://doaj.org/article/b05e420a77464a9895f3e24a104f6288
Publikováno v:
IEEE Access, Vol 12, Pp 151856-151863 (2024)
Numerical models have long been used to understand geoscientific phenomena, including tidal currents, crucial for renewable energy production and coastal engineering. However, their computational cost hinders generating data of varying resolutions. A
Externí odkaz:
https://doaj.org/article/e0c8cbf4f581432c81f2b907ef44f1f0
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 14935-14948 (2024)
In the field of remote sensing, it is not feasible to obtain high spatial resolution multispectral (HRMS) images from a single satellite sensor. The existing methods use pansharpening techniques to obtain HRMS images by fusing panchromatic (PAN) and
Externí odkaz:
https://doaj.org/article/1a51b2f552c24aa09bbf7be04c42d693
Autor:
Han-Nyoung Lee, Hak Gu Kim
Publikováno v:
IEEE Access, Vol 12, Pp 14314-14323 (2024)
Photometric stereo, which derives per-pixel surface normals from shading cues, faces challenges in capturing high-resolution (HR) images in linear response systems. We address the representation of HR surface normals from low-resolution (LR) photomet
Externí odkaz:
https://doaj.org/article/dea46971bda14bd5b3eacdf9a5e00284
Autor:
Dongshen Han, Chaoning Zhang
Publikováno v:
Remote Sensing, Vol 16, Iss 23, p 4473 (2024)
Image Implicit Neural Representations (INRs) adopt a neural network to learn a continuous function for mapping the pixel coordinates to their corresponding values. This task has gained significant attention for representing images in a continuous man
Externí odkaz:
https://doaj.org/article/66618d76321c4bedaf561689dd6ec56c
Autor:
Dongshen Han, Chaoning Zhang
Publikováno v:
Remote Sensing, Vol 16, Iss 23, p 4471 (2024)
Implicit neural representations (INRs) are a new way to represent all kinds of signals ranging from 1D audio to 3D shape signals, among which 2D images are the most widely explored due to their ubiquitous presence. Image INRs utilize a neural network
Externí odkaz:
https://doaj.org/article/1bc6392b0ebb4fba9eef2eb53ad021a9
Publikováno v:
Applied Sciences, Vol 14, Iss 22, p 10685 (2024)
Numerical simulation in fluid dynamics can be computationally expensive and difficult to achieve. To enhance efficiency, developing high-performance and accurate surrogate models is crucial, where deep learning shows potential. This paper introduces
Externí odkaz:
https://doaj.org/article/00a3c8c7cd8f4f87b0d1757d8e2e9ac6
Publikováno v:
物联网学报, Vol 7, Pp 35-42 (2023)
Implicit neural representation characterizes the mapping between the signal’s coordinate to its attributes, and has been widely used in the optimization of inverse problems by embedding the physics process into the loss function.However, the implic
Externí odkaz:
https://doaj.org/article/19e8271235e546dc81d2b01b2059552f
Publikováno v:
IEEE Access, Vol 11, Pp 132867-132877 (2023)
Single image super-resolution (SISR) with deep convolutional neural networks has recently attracted increasing attention due to its potentials to generate rich details. To obtain better fidelity and visual quality, most of existing methods are of hea
Externí odkaz:
https://doaj.org/article/072a64af10f34926b63386877ea26e29