Hybrid Technique for Constructing Footprint Extraction System from Satellite Imaginary

Hybrid Technique for Constructing Footprint Extraction System from Satellite Imaginary

The building extraction of the footprint from the satellite imagination has been a research problem that needs to be solved efficiently. The hybrid semantic segmentation framework is used to increase the footprint extraction system as the Inria Aerial Image Labeling Dataset is involved in improving...

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Bibliographic Details
Published in:2024 2nd International Conference on Networking and Communications (ICNWC) pp. 1 - 4
Main Authors: Raghavendran, N., Menaga, P., Prabu, V. Vignesh, Manimaran, V., Robinson, Y. Harold, Ramanan, K.
Format: Conference Proceeding
Language:English
Published: IEEE 02-04-2024
Subjects:
Buildings
CGAN
Data augmentation
Data models
Footprint extraction
GIS
Instance segmentation
Mask RCNN
Performance evaluation
Satellites
Semantic segmentation
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Summary:The building extraction of the footprint from the satellite imagination has been a research problem that needs to be solved efficiently. The hybrid semantic segmentation framework is used to increase the footprint extraction system as the Inria Aerial Image Labeling Dataset is involved in improving the extraction of the footprint, the proposed technique is framed with the CGAN model and Mask RCNN for utilizing the instance segmentation which manages the data augmentation and semantic segmentation process. The performance evaluation shows that the proposed technique has an improved F1 score and accuracy as the effect of every functionality for the footprint extraction has been analyzed subsequently.
DOI:10.1109/ICNWC60771.2024.10537388