Search results for "Spectral data"
showing 6 items of 56 documents
Four new eremophilendiolides from Ligularia atroviolacea
2007
From Ligularia atroviolacea, four new eremophilendiolides, 8 beta-hydroxy-eremophil-3,7 (11)-dien-12,8 alpha(14,6 alpha)-diolide (1), 8 beta-methoxy-eremophil-3,7(11)-dien-12,8 alpha(14,6 alpha)-diolide (2), 8 alpha-hydroxy-eremophil-3,7(11)-dien-12,8 beta(14,6 alpha)-diolide (3) and eremophil-3,7(11),8-trien-12,8 (14,6 alpha)-diolide (4), as well as a known diolide (5) were isolated. Their structures were elucidated on the basis of 1D and 2D NMR as well as ESI-MS spectral data. (c) 2006 Yu Zhao. Published by Elsevier B.V. on behalf of Chinese Chemical Society. All rights reserved.
CLUSTERING INCOMPLETE SPECTRAL DATA WITH ROBUST METHODS
2018
Abstract. Missing value imputation is a common approach for preprocessing incomplete data sets. In case of data clustering, imputation methods may cause unexpected bias because they may change the underlying structure of the data. In order to avoid prior imputation of missing values the computational operations must be projected on the available data values. In this paper, we apply a robust nan-K-spatmed algorithm to the clustering problem on hyperspectral image data. Robust statistics, such as multivariate medians, are more insensitive to outliers than classical statistics relying on the Gaussian assumptions. They are, however, computationally more intractable due to the lack of closed-for…
Multispectral analysis of color vision deficiency tests
2011
Color deficiency tests are usually produced by means of polygraphy technologies and help to diagnose the type and severity of the color deficiencies. Due to different factors, as lighting conditions or age of the test, standard characteristics of these tests fail, thus not allowing diagnosing unambiguously the degree of different color deficiency. Multispectral camera was used to acquire the spectral images of the Ishihara and Rabkin pseudoisochromatic plates in the visible spectrum. Spectral data was converted to cone signals, and successive mathematics applied to provide a simple simulation of the test performance. Colorimetric data of the each pixel of the test image can be calculated an…
Tree Species Identification Using 3D Spectral Data and 3D Convolutional Neural Network
2018
In this study we apply 3D convolutional neural network (CNN) for tree species identification. Study includes the three most common Finnish tree species. Study uses a relatively large high-resolution spectral data set, which contains also a digital surface model for the trees. Data has been gathered using an unmanned aerial vehicle, a framing hyperspectral imager and a regular RGB camera. Achieved classification results are promising by with overall accuracy of 96.2 % for the classification of the validation data set. nonPeerReviewed
Synthesis, NMR spectral and structural studies on mixed ligand complexes of Pd(II) dithiocarbamates: First structural report on palladium(II) dithioc…
2016
Abstract Three new mixed ligand complexes of palladium(II) dithiocarbamates; [Pd(4-dpmpzdtc)(PPh3)(SCN)] (1), [Pd(4-dpmpzdtc)(PPh3)Cl] (2) and [Pd(bzbudtc)(PPh3)Cl] (3), (where, 4-dpmpzdtc = 4-(diphenylmethyl)piperazinecarbodithioato anion, bzbudtc = N-benzyl-N-butyldithiocarbamato anion and PPh3 = triphenylphosphine) have been synthesized from their respective parent dithiocarbamates by ligand exchange reactions and characterized by IR and NMR (1H, 13C and 31P) spectroscopy. IR and NMR spectral data support the isobidentate coordination of the dithiocarbamate ligands in all complexes (1–3) in solid and in solution, respectively. Single crystal diffraction analysis of complexes 1–3 evidence…
UAV-based hyperspectral monitoring of small freshwater area
2014
Recent development in compact, lightweight hyperspectral imagers have enabled UAV-based remote sensing with reasonable costs. We used small hyperspectral imager based on Fabry-Perot interferometer for monitoring small freshwater area in southern Finland. In this study we shortly describe the utilized technology and the field studies performed. We explain processing pipeline for gathered spectral data and introduce target detection-based algorithm for estimating levels of algae, aquatic chlorophyll and turbidity in freshwater. Certain challenges we faced are pointed out.