Johanna Ärje
Johanna Ärje
Tampere University
Verified email at tuni.fi
Title
Cited by
Cited by
Year
Tieto-ja viestintätekniikan merkitys ja käyttömahdollisuudet koulun arjessa
M Kankaanranta, T Palonen, T Kejonen, J Ärje
Teoksessa M. Kankaanranta (toim.) Opetusteknologia koulun arjessa …, 2011
462011
Classification and retrieval on macroinvertebrate image databases
S Kiranyaz, T Ince, J Pulkkinen, M Gabbouj, J Ärje, S Kärkkäinen, ...
Computers in biology and medicine 41 (7), 463-472, 2011
412011
Evaluating the performance of artificial neural networks for the classification of freshwater benthic macroinvertebrates
H Joutsijoki, K Meissner, M Gabbouj, S Kiranyaz, J Raitoharju, J Ärje, ...
Ecological Informatics 20, 1-12, 2014
222014
Statistical classification and proportion estimation-an application to a macroinvertebrate image database
J Ärje, S Kärkkäinen, K Meissner, T Turpeinen
2010 IEEE International Workshop on Machine Learning for Signal Processing …, 2010
102010
Benchmark database for fine-grained image classification of benthic macroinvertebrates
J Raitoharju, E Riabchenko, I Ahmad, A Iosifidis, M Gabbouj, S Kiranyaz, ...
Image and Vision Computing 78, 73-83, 2018
92018
The effect of automated taxa identification errors on biological indices
J Ärje, S Kärkkäinen, K Meissner, A Iosifidis, T Ince, M Gabbouj, ...
Expert systems with applications 72, 108-120, 2017
82017
Breaking the curse of dimensionality in quadratic discriminant analysis models with a novel variant of a Bayes classifier enhances automated taxa identification of freshwater …
J Ärje, S Kärkkäinen, T Turpeinen, K Meissner
Environmetrics 24 (4), 248-259, 2013
82013
Understanding the statistical properties of the percent model affinity index can improve biomonitoring related decision making
J Ärje, KP Choi, F Divino, K Meissner, S Kärkkäinen
Stochastic Environmental Research and Risk Assessment 30 (7), 1981-2008, 2016
72016
Automatic image‐based identification and biomass estimation of invertebrates
J Ärje, C Melvad, MR Jeppesen, SA Madsen, J Raitoharju, ...
Methods in Ecology and Evolution 11 (8), 922-931, 2020
62020
Human experts vs. machines in taxa recognition
J Ärje, J Raitoharju, A Iosifidis, V Tirronen, K Meissner, M Gabbouj, ...
arXiv preprint arXiv:1708.06899, 2017
62017
Dynamics and temporal changes in suspended sediment transport in northern Finland: transport of very fine particulate matter
H Marttila, ML Nieminen, J Ärje, K Meissner, T Tuukkanen, J Saukkoriipi, ...
Boreal Environment Publishing Board, 2016
42016
Yliopistojen tutkintokoulutuksen ja tutkimuksen rahoitus ja tulokset vuosina 2000-2004 ja 2005-2009
P Neittaanmäki, T Tiihonen, J Ärje, R Neittaanmäki
Tutkimusselosteita/Koulutuksen tutkimuslaitos, 2010
32010
Deep learning and computer vision will transform entomology
TT Hoye, J Arje, K Bjerge, OLP Hansen, A Iosifidis, F Leese, H Mann, ...
bioRxiv, 2020
12020
Automatic flower detection and classification system using a light-weight convolutional neural network
J Arjea, D Miliorisd, DT Tranb, JU Jepsene, J Raitoharjub, M Gabboujb, ...
EUSIPCO workshop on Signal Processing, Computer Vision and Deep Learning for …, 2019
12019
Improving statistical classification methods and ecological status assessment for river macroinvertebrates
J Ärje
Report/University of Jyväskylä. Department of Mathematics and Statistics, 2016
12016
Climate sensitivity of tundra plant-pollinator interactions tracked by computer vision
HMR Mann, J Ärje, A Iosifidis, TT Høye
Entomology 2019, 2019
2019
Automatic identification of arctic arthropods
J Ärje, A Iosifidis, K Meissner, J Raitoharju, SA Madsen, MR Jeppesen, ...
Entomology 2019, 2019
2019
Empirical Bayes improves assessments of diversity and similarity when overdispersion prevails in taxonomic counts with no covariates
F Divino, J Ärje, A Penttinen, K Meissner, S Kärkkäinen
Ecological Indicators 106, 105413, 2019
2019
Automatic Flower Detection and Classification System Uing a Light-Weight Convolutional Neural Network
J Ärje, D Milioris, DT Tran, JU Jepsen, J Raitoharju, M Gabbouj, A Iosifidis, ...
European Signal Processing Conference 2019, 2019
2019
Empirical Bayes to assess ecological diversity and similarity with overdispersion in multivariate counts
F Divino, J Ärje, A Penttinen, K Meissner, S Kärkkäinen
arXiv preprint arXiv:1810.04748, 2018
2018
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Articles 1–20