Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Alexandros Sopasakis"'
Autor:
Alexandros Sopasakis, Maria Nilsson, Mattias Askenmo, Fredrik Nyholm, Lillemor Mattsson Hultén, Victoria Rotter Sopasakis
Publikováno v:
PLoS ONE, Vol 19, Iss 4, p e0299600 (2024)
Serum electrophoresis (SPEP) is a method used to analyze the distribution of the most important proteins in the blood. The major clinical question is the presence of monoclonal fraction(s) of antibodies (M-protein/paraprotein), which is essential for
Externí odkaz:
https://doaj.org/article/a970f38f35b1497ba275787fc5abfa6e
Publikováno v:
Smart Agricultural Technology, Vol 3, Iss , Pp 100107- (2023)
We built machine learning and image analysis tools in order to forecast winter wheat yield based on a rich multi dimensional tensor of agricultural information spanning different scales. This information consists of satellite multi-band images, local
Externí odkaz:
https://doaj.org/article/167b2b35aeb84bcf8ec490bbddeba065
Publikováno v:
Agriculture, Vol 13, Iss 4, p 801 (2023)
We train and compare the performance of two machine learning methods, a multi-variate regression network and a ResNet-50-based neural network, to learn and forecast plant biomass as well as the relative growth rate from a short sequence of temporal i
Externí odkaz:
https://doaj.org/article/c6e9fcff10e74f609a50e94484d067a7
Autor:
Oliver Persson Bogdanovski, Christoffer Svenningsson, Simon Månsson, Andreas Oxenstierna, Alexandros Sopasakis
Publikováno v:
Agriculture, Vol 13, Iss 4, p 813 (2023)
We train and compare the performance of two different machine learning algorithms to learn changes in winter wheat production for fields from the southwest of Sweden. As input to these algorithms, we use cloud-penetrating Sentinel-1 polarimetry radar
Externí odkaz:
https://doaj.org/article/9e4a1d809bee49f694cb0d5922d6779f
Autor:
Karl Tengelin, Alexandros Sopasakis
Publikováno v:
National Accounting Review, Vol 2, Iss 4, Pp 354-366 (2020)
We establish support and resistance levels from data in intraday currency exchange market activity based on machine learning methods. Specifically we design two semi-supervised classification neural networks. The first one is based on a variant of th
Externí odkaz:
https://doaj.org/article/5a83632f97234008a802b269bc783673
Publikováno v:
MLSP
Millimeter-wave cellular communication requires beamforming procedures that enable alignment of the transmitter and receiver beams as the user equipment (UE) moves. For efficient beam tracking it is advantageous to classify users according to their t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a87bcf778e44d2d8790d15d612179fd5
http://arxiv.org/abs/2109.05893
http://arxiv.org/abs/2109.05893
Publikováno v:
Intelligent Systems in Industrial Applications ISBN: 9783030671471
ISMIS (Industrial Paper)
ISMIS (Industrial Paper)
We compare classic scalar temporal difference learning with three new distributional algorithms for playing the game of 5-in-a-row using deep neural networks: distributional temporal difference learning with constant learning rate, and two distributi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c961e01261ba45494942c3e7af5254bf
https://doi.org/10.1007/978-3-030-67148-8_14
https://doi.org/10.1007/978-3-030-67148-8_14
Autor:
Alexandros Sopasakis
Publikováno v:
Contributions to Statistics ISBN: 9783030562182
We optimize traffic signal timing sequences for a section of a traffic network in order to reduce congestion based on anticipated demand. The system relies on the accuracy of the predicted traffic demand in time and space which is carried out by a ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::43d65edfd0b580541fa6c9e2a26c5648
https://doi.org/10.1007/978-3-030-56219-9_19
https://doi.org/10.1007/978-3-030-56219-9_19
Publikováno v:
Transportation Research Part B: Methodological. 86:1-18
We develop theoretical and computational tools which can appraise traffic flow models and optimize their performance against current time-series traffic data and prevailing conditions. The proposed methodology perturbs the parameter space and underta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91acb183c355ef835d4baeb19444d988
https://doi.org/10.1016/j.trb.2016.01.003
https://doi.org/10.1016/j.trb.2016.01.003
Autor:
Alexandros Sopasakis
Publikováno v:
Procedia - Social and Behavioral Sciences. 80:837-845
We introduce a novel lattice-free stochastic process which models vehicular traffic at the microscopic level. Vehicles are allowed to advance freely within their lane or change lanes without the limitation of lattice cells. Vehicles move under the in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a44e8f086c3255c61d91ce482c978d5
https://doi.org/10.1016/j.sbspro.2013.05.045
https://doi.org/10.1016/j.sbspro.2013.05.045