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Building detection with convolutional networks trained with transfer learning = Zaznavanje stavb z uporabo nevronskih mrež, učenih s prenosom znanjaŠanca, Simon ; Oštir, Krištof ; Mangafić, AlenBuilding footprint detection based on orthophotos can be used to update the building cadastre. In recent years deep learning methods using convolutional neural networks have been increasingly used ... around the world. We present an example of automatic building classification using our datasets made of colour near-infrared orthophotos (NIRR-G) and colour orthophotos (R-G-B). Building detection using pretrained weights from two large scale datasets Microsoft Common Objects in Context (MS COCO) and ImageNet was performed and tested. We applied the Mask Region Convolutional Neural Network (Mask R-CNN) to detect the building footprints. The purpose of our research is to identify the applicability of pre-trained neural networks on the data of another colour space to build a classification model without re-learning.Vir: Geodetski vestnik : glasilo Zveze geodetov Slovenije = Journal of the Association of Surveyors of Slovenia. - ISSN 0351-0271 (Letn. 65, št. 4, 2021, str. 559-593)Vrsta gradiva - članek, sestavni delLeto - 2021Jezik - angleški, slovenskiCOBISS.SI-ID - 92864259
Avtor
Šanca, Simon |
Oštir, Krištof |
Mangafić, Alen
Teme
deep learning |
convolutional neural networks |
classification of buildings |
Mask R-CNN |
object detection |
object segmentation, |
automatic classification |
globoko učenje |
konvolucijske nevronske mreže |
klasifikacija stavb |
Mask R-CNN |
detekcija objektov |
segmentacija objektov |
samodejna klasifikacija
vir: Geodetski vestnik : glasilo Zveze geodetov Slovenije = Journal of the Association of Surveyors of Slovenia. - ISSN 0351-0271 (Letn. 65, št. 4, 2021, str. 559-593)
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Povezave do osebnih bibliografij avtorjev | Povezave do podatkov o raziskovalcih v sistemu SICRIS |
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Šanca, Simon | |
Oštir, Krištof | 15112 |
Mangafić, Alen | 51608 |
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