Search results for "spektri"

Assessment of nonnegative matrix factorization algorithms for electroencephalography spectral analysis.

2020

AbstractBackgroundNonnegative matrix factorization (NMF) has been successfully used for electroencephalography (EEG) spectral analysis. Since NMF was proposed in the 1990s, many adaptive algorithms have been developed. However, the performance of their use in EEG data analysis has not been fully compared. Here, we provide a comparison of four NMF algorithms in terms of accuracy of estimation, stability (repeatability of the results) and time complexity of algorithms with simulated data. In the practical application of NMF algorithms, stability plays an important role, which was an emphasis in the comparison. A Hierarchical clustering algorithm was implemented to evaluate the stability of NM…

Updating strategies for distance based classification model with recursive least squares

2022

Abstract. The idea is to create a self-learning Minimal Learning Machine (MLM) model that is computationally efficient, easy to implement and performs with high accuracy. The study has two hypotheses. Experiment A examines the possibilities of introducing new classes with Recursive Least Squares (RLS) updates for the pre-trained self learning-MLM model. The idea of experiment B is to simulate the push broom spectral imagers working principles, update and test the model based on a stream of pixel spectrum lines on a continuous scanning process. Experiment B aims to train the model with a significantly small amount of labelled reference points and update it continuously with (RLS) to reach ma…

Editorial for the Special Issue “Frontiers in Spectral Imaging and 3D Technologies for Geospatial Solutions”

2019

This Special Issue hosts papers on the integrated use of spectral imaging and 3D technologies in remote sensing, including novel sensors, evolving machine learning technologies for data analysis, and the utilization of these technologies in a variety of geospatial applications. The presented results showed improved results when multimodal data was used in object analysis.

Hyperspectral imaging in detecting dermal invasion in lentigo maligna melanoma

2017

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

Assessment of microalgae species, biomass, and distribution from spectral images using a convolution neural network

2022

AbstractEffective monitoring of microalgae growth is crucial for environmental observation, while the applications of this monitoring could also be expanded to commercial and research-focused microalgae cultivation. Currently, the distinctive optical properties of different microalgae groups are targeted for monitoring. Since different microalgae can grow together, their spectral signals are mixed with ambient properties, making estimations of species biomasses a challenging task. In this study, we cultured five different microalgae and monitored their growth with a mobile spectral imager in three separate experiments. We trained and validated a one-dimensional convolution neural network by…

Solar UV radiation and plant responses : assessing the methodological problems in research concerning stratospheric ozone depletion

2010

Rare beta decays and the spectrum-shape method

2017

This is a thesis consisting of seven publications and an introductory part on theoretical studies on rare single beta decays. Firstly, the theoretical framework is applied to the computation of partial half-lives for few selected cases of rare single beta-decay transitions. This includes the study on a possible ultra-low-Q-value decay branch of 115Cd as well as the highly forbidden beta decays of 48Ca and 50V. The double magic 48Ca is one of the few experimentally verified nuclei that decay via the two-neutrino mode of double beta decay. A theoretical study on the single beta-decay branches was used to inspect the competition between the single and double beta-decay channels. In the case of…

Hyperspectral Imaging of Macroinvertebrates : a Pilot Study for Detecting Metal Contamination in Aquatic Ecosystems

2018

The applicability of spectral analysis in detection of freshwater metal contamination was assessed by developing and testing a novel hyperspectral imaging (HSI) application for aquatic insect larvae (Trichoptera: Hydropsychidae). Larvae were first exposed to four different cadmium (Cd) concentrations: 0, 1, 10, and 100 μg L−1 for 96 h. Individual larvae were then preserved in ethanol, inspected with microscopy for the number of anomalies in larval gills, and imaged by hyperspectral camera operating with wavebands between 500 and 850 nm. Three additional larvae from each exposure were analyzed for tissue Cd concentration. Although the larval tissue Cd concentrations correlated positively wit…

HYPERBLEND: SIMULATING SPECTRAL REFLECTANCE AND TRANSMITTANCE OF LEAF TISSUE WITH BLENDER

2022

Abstract. Remotely sensing vegetation condition and health hazards requires modeling the connection of plants’ biophysical and biochemical parameters to their spectral response. Even though many models exist already, the field suffers from lack of access to program code. In this study, we will assess the feasibility of open-source 3D-modeling and rendering software Blender in simulating hyperspectral reflectance and transmittance of leaf tissue to serve as a base for a more advanced large-scale simulator. This is the first phase of a larger HyperBlend project, which will provide a fully open-source, canopy scale leaf optical properties model for simulating remotely sensed hyperspectral imag…