Zobrazeno 1 - 10 of 17 pro vyhledávání: '"Yi‐Tun Lin"'
1
Akademický článek
A Rehabilitation of Pixel-Based Spectral Reconstruction from RGB Images
Autor: Yi-Tun Lin, Graham D. Finlayson
Publikováno v: Sensors, Vol 23, Iss 8, p 4155 (2023)
Recently, many deep neural networks (DNN) have been proposed to solve the spectral reconstruction (SR) problem: recovering spectra from RGB measurements. Most DNNs seek to learn the relationship between an RGB viewed in a given spatial context and it
Externí odkaz: https://doaj.org/article/a079096939b740609868bf9aa7697ab2
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2
Akademický článek
On the Optimization of Regression-Based Spectral Reconstruction
Autor: Yi-Tun Lin, Graham D. Finlayson
Publikováno v: Sensors, Vol 21, Iss 16, p 5586 (2021)
Spectral reconstruction (SR) algorithms attempt to recover hyperspectral information from RGB camera responses. Recently, the most common metric for evaluating the performance of SR algorithms is the Mean Relative Absolute Error (MRAE)—an ℓ1 rela
Externí odkaz: https://doaj.org/article/20e06978ac3a4b72a70b8debd736dce9
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3
Akademický článek
Physically Plausible Spectral Reconstruction
Autor: Yi-Tun Lin, Graham D. Finlayson
Publikováno v: Sensors, Vol 20, Iss 21, p 6399 (2020)
Spectral reconstruction algorithms recover spectra from RGB sensor responses. Recent methods—with the very best algorithms using deep learning—can already solve this problem with good spectral accuracy. However, the recovered spectra are physical
Externí odkaz: https://doaj.org/article/2ce0be060e7e4683be5ce2c9b7165549
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7
Investigating the upper-bound performance of sparse-coding-based spectral reconstruction from RGB images
Autor: Yi-Tun Lin, Graham D. Finlayson
In Spectral Reconstruction (SR), we recover hyperspectral images from their RGB counterparts. Most of the recent approaches are based on Deep Neural Networks (DNN), where millions of parameters are trained mainly to extract and utilize the contextual
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2378a1276407c49f0dc1a5d8f3734925
https://ueaeprints.uea.ac.uk/id/eprint/82552/
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8
Dissertation/ Thesis
The influence of p-type a-SiC:H layers on the performance of a-Si:H thin film solar cells
Autor: Yi-Tun Lin, 林義敦
95
In this thesis, double p-type hydrogenated amorphous silicon carbine ( a-SiC:H(B) ) layers P1-P2-I-N solar cells are fabricated by plasma-enhances chemical vapor deposition with pulse-wave modulation RF power. Changing CH4 and B2H6 gas flow [
Externí odkaz: http://ndltd.ncl.edu.tw/handle/02559827293576706866
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9
On the Optimization of Regression-Based Spectral Reconstruction
Autor: Graham D. Finlayson, Yi-Tun Lin
Publikováno v: Sensors, Vol 21, Iss 5586, p 5586 (2021)
Sensors (Basel, Switzerland)
Sensors
Volume 21
Issue 16
Spectral reconstruction (SR) algorithms attempt to recover hyperspectral information from RGB camera responses. Recently, the most common metric for evaluating the performance of SR algorithms is the Mean Relative Absolute Error (MRAE)—an ℓ1 rela
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aca82c49ead337348876a770716ce6ef
https://www.mdpi.com/1424-8220/21/16/5586
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10
Reconstructing spectra from RGB images by relative error least-squares regression
Autor: Graham D. Finlayson, Yi-Tun Lin
Spectral reconstruction (SR) algorithms attempt to map RGB- to hyperspectral-images. Classically, simple pixel-based regression is used to solve for this SR mapping and more recently patch-based Deep Neural Networks (DNN) are considered (with a modes
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e1eecc9534b7b8055a10d512d813d700
https://ueaeprints.uea.ac.uk/id/eprint/80300/
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