In:
Geodetski vestnik, University of Ljubljana, Vol. 64, No. 04 ( 2021), p. 559-593
Abstract:
Building 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 (NIR-R-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.
Type of Medium:
Online Resource
ISSN:
0351-0271
Uniform Title:
Zaznavanje stavb z uporabo nevronskih mrež, učenih s prenosom znanja
DOI:
10.15292/geodetski-vestnik-2021-04
DOI:
10.15292/geodetski-vestnik.
DOI:
10.15292/geodetski-vestnik.2021.04.559-593
Language:
Unknown
Publisher:
University of Ljubljana
Publication Date:
2021
detail.hit.zdb_id:
2049721-0
