0000000000515138

AUTHOR

Jyri Hamalainen

showing 2 related works from this author

Reinforcement Learning Based Mobility Load Balancing with the Cell Individual Offset

2021

In this study, we focus on the cell individual offset (CIO) parameter in the handover process, which represents the willingness of a cell to admit the incoming handovers. However, it is challenging to tune the CIO parameter, as any poor implementation can lead to undesired outcomes, such as making the neighboring cells over-loaded while decreasing the traffic load of the cell. In this work, a reinforcement learning-based approach for parameter selection is introduced, since it is quite convenient for dynamically changing environments. In that regard, two different techniques, namely Q-learning and SARSA, are proposed, as they are known for their multi-objective optimization capabilities. Mo…

Mathematical optimizationOffset (computer science)Computer science05 social sciences050801 communication & media studies020206 networking & telecommunicationsSelf-organizing network02 engineering and technologyLoad balancing (computing)Load management0508 media and communicationsHandoverMetric (mathematics)0202 electrical engineering electronic engineering information engineeringBenchmark (computing)Reinforcement learning2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)
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PRACTICAL APPROACH FOR HYPERSPECTRAL IMAGE PROCESSING IN PYTHON

2018

Abstract. Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor and a spectral index library. They also fulfill our goal of easy and agile data processing. In this paper we will present our processing pipeline and demonstrate it in practice.

lcsh:Applied optics. Photonicsmedicine.medical_specialtySoftware_GENERALhyperspectral imagingComputer sciencedata analysis0208 environmental biotechnologyImage processing02 engineering and technologykuvankäsittelylcsh:Technologyopen sourceavoin lähdekoodimedicinecomputer.programming_languagelcsh:Tbusiness.industrylcsh:TA1501-1820Hyperspectral imagingPython (programming language)Hyperspectral image processing020801 environmental engineeringSpectral imagingpythonkoneoppiminenlcsh:TA1-2040lcsh:Engineering (General). Civil engineering (General)businessSoftware engineeringcomputerAgile software developmentThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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