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Ilkka Pölönen
Ilkka Pölönen
Associate Professor (Computational Data Analysis), Faculty of Information Technology
Verified email at jyu.fi - Homepage
Title
Cited by
Cited by
Year
Processing and assessment of spectrometric, stereoscopic imagery collected using a lightweight UAV spectral camera for precision agriculture
E Honkavaara, H Saari, J Kaivosoja, I Pölönen, T Hakala, P Litkey, ...
Remote Sensing 5 (10), 5006-5039, 2013
5772013
Individual tree detection and classification with UAV-based photogrammetric point clouds and hyperspectral imaging
O Nevalainen, E Honkavaara, S Tuominen, N Viljanen, T Hakala, X Yu, ...
Remote sensing 9 (3), 185, 2017
4792017
Tree species classification of drone hyperspectral and RGB imagery with deep learning convolutional neural networks
S Nezami, E Khoramshahi, O Nevalainen, I Pölönen, E Honkavaara
Remote Sensing 12 (7), 1070, 2020
1772020
Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a …
E Honkavaara, MA Eskelinen, I Pölönen, H Saari, H Ojanen, R Mannila, ...
IEEE Transactions on Geoscience and Remote Sensing 54 (9), 5440-5454, 2016
942016
Spectral imaging from UAVs under varying illumination conditions
T Hakala, E Honkavaara, H Saari, J Mäkynen, J Kaivosoja, L Pesonen, ...
International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2013
862013
Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV
I Pölönen, H Saari, J Kaivosoja, E Honkavaara, L Pesonen
Remote sensing for agriculture, ecosystems, and hydrology XV 8887, 141-149, 2013
792013
Unmanned aerial system imagery and photogrammetric canopy height data in area-based estimation of forest variables
S Tuominen, A Balazs, H Saari, I Pölönen, J Sarkeala, R Viitala
Silva Fennica 49 (5), 2015
712015
Assessment of classifiers and remote sensing features of hyperspectral imagery and stereo-photogrammetric point clouds for recognition of tree species in a forest area of high …
S Tuominen, R Näsi, E Honkavaara, A Balazs, T Hakala, N Viljanen, ...
Remote Sensing 10 (5), 714, 2018
702018
Detecting field cancerization using a hyperspectral imaging system
N Neittaanmäki‐Perttu, M Grönroos, T Tani, I Pölönen, A Ranki, ...
Lasers in surgery and medicine 45 (7), 410-417, 2013
632013
Using VIS/NIR and IR spectral cameras for detecting and separating crime scene details
J Kuula, I Pölönen, HH Puupponen, T Selander, T Reinikainen, ...
Sensors, and Command, Control, Communications, and Intelligence (C3I …, 2012
572012
Miniaturized hyperspectral imager calibration and UAV flight campaigns
H Saari, I Pölönen, H Salo, E Honkavaara, T Hakala, C Holmlund, ...
Sensors, systems, and next-generation satellites xvii 8889, 448-459, 2013
512013
A case study of a precision fertilizer application task generation for wheat based on classified hyperspectral data from UAV combined with farm history data
J Kaivosoja, L Pesonen, J Kleemola, I Pölönen, H Salo, E Honkavaara, ...
Remote Sensing for Agriculture, Ecosystems, and Hydrology XV 8887, 118-127, 2013
452013
Delineating margins of lentigo maligna using a hyperspectral imaging system
N Neittaanmäki-Perttu, M Gronroos, L Jeskanen, I Polonen, A Ranki, ...
Acta dermato-venereologica 95 (5), 549-552, 2015
442015
DeepFake knee osteoarthritis X-rays from generative adversarial neural networks deceive medical experts and offer augmentation potential to automatic classification
F Prezja, J Paloneva, I Pölönen, E Niinimäki, S Äyrämö
Scientific Reports 12 (1), 18573, 2022
432022
Hyperspectral imaging system in the delineation of Ill‐defined basal cell carcinomas: a pilot study
M Salmivuori, N Neittaanmäki, I Pölönen, L Jeskanen, E Snellman, ...
Journal of the European Academy of Dermatology and Venereology 33 (1), 71-78, 2019
392019
Hyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables
S Tuominen, A Balazs, E Honkavaara, I Pölönen, H Saari, T Hakala, ...
Silva Fennica 51 (5), 2017
382017
Delineation of malignant skin tumors by hyperspectral imaging using diffusion maps dimensionality reduction
V Zheludev, I Pölönen, N Neittaanmäki-Perttu, A Averbuch, ...
Biomedical Signal Processing and Control 16, 48-60, 2015
382015
Hyperspectral imaging reveals spectral differences and can distinguish malignant melanoma from pigmented basal cell carcinomas: a pilot study
J Räsänen, M Salmivuori, I Pölönen, M Grönroos, N Neittaanmäki
Acta dermato-venereologica 101 (2), 2021
322021
Convolutional neural networks in skin cancer detection using spatial and spectral domain
I Pölönen, S Rahkonen, L Annala, N Neittaanmäki
Photonics in Dermatology and Plastic Surgery 2019 10851, 21-28, 2019
272019
Autonomous hyperspectral UAS photogrammetry for environmental monitoring applications
E Honkavaara, T Hakala, L Markelin, A Jaakkola, H Saari, H Ojanen, ...
ISPRS Archives, 2014
262014
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