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Authors: R. Avenash and P. Viswanath

Affiliation: Computer Science and Engineering, Indian Institute of Information Technology, Chittoor, Sri City, A.P. and India

ISBN: 978-989-758-354-4

Keyword(s): Semantic Segmentation, Activation Function, Remote Sensing Images, Convolutional Neural Networks.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Segmentation and Grouping

Abstract: Remote sensing is a key strategy used to obtain information related to the Earth’s resources and its usage patterns. Semantic segmentation of a remotely sensed image in the spectral, spatial and temporal domain is an important preprocessing step where different classes of objects like crops, water bodies, roads, buildings are localized by a boundary. The paper proposes to use the Convolutional Neural Network (CNN) called U-HardNet with a new and novel activation function called the Hard-Swish for segmenting remotely sensed images. Along with the CNN, for a precise localization, the paper proposes to use IHS transformed images with binary cross entropy loss minimization. Experiments are done with publicly available images provided by DSTL (Defence Science and Technology Laboratory) for object recognition and a comparison is drawn with some recent relevant techniques.

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Paper citation in several formats:
Avenash, R. and Viswanath, P. (2019). Semantic Segmentation of Satellite Images using a Modified CNN with Hard-Swish Activation Function.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, ISBN 978-989-758-354-4, pages 413-420. DOI: 10.5220/0007469604130420

@conference{visapp19,
author={R. Avenash. and P. Viswanath.},
title={Semantic Segmentation of Satellite Images using a Modified CNN with Hard-Swish Activation Function},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP,},
year={2019},
pages={413-420},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007469604130420},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP,
TI - Semantic Segmentation of Satellite Images using a Modified CNN with Hard-Swish Activation Function
SN - 978-989-758-354-4
AU - Avenash, R.
AU - Viswanath, P.
PY - 2019
SP - 413
EP - 420
DO - 10.5220/0007469604130420

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