Domain Shift in Capsule Networks

Rajath S.; Sumukh Aithal K.; S. Natarajan

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Paper

Domain Shift in Capsule Networks

Topics: Deep Learning and Neural Networks; Machine Learning Methods; Shape Representation

In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods ICPRAM - Volume 1, 275-278, 2021

Authors: Rajath S. ; Sumukh Aithal K. and S. Natarajan

Affiliation: Department of Computer Science, PES University, Bangalore, India

Keyword(s): Capsule Networks, Domain Shift, Convolutional Neural Networks.

Abstract: Capsule Networks are an exciting deep learning architecture which overcomes some of the shortcomings of Convolutional Neural Networks (CNNs). Capsule networks aim to capture spatial relationships between parts of an object and exhibits viewpoint invariance. In practical computer vision, the training data distribution is different from the test distribution and the covariate shift affects the performance of the model. This problem is called Domain Shift. In this paper, we analyze how well capsule networks adapt to new domains by experimenting with multiple routing algorithms and comparing it with CNNs.

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 18.220.59.69

In the current month:

Recent papers: 100 available of 100 total

2⁺ years older papers: 200 available of 200 total

Paper citation in several formats:

S., R.; K., S. and Natarajan, S. (2021). Domain Shift in Capsule Networks. In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-486-2; ISSN 2184-4313, SciTePress, pages 275-278. DOI: 10.5220/0010252002750278

@conference{icpram21,
author={Rajath S.. and Sumukh Aithal K.. and S. Natarajan.},
title={Domain Shift in Capsule Networks},
booktitle={Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2021},
pages={275-278},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010252002750278},
isbn={978-989-758-486-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Domain Shift in Capsule Networks
SN - 978-989-758-486-2
IS - 2184-4313
AU - S., R.
AU - K., S.
AU - Natarajan, S.
PY - 2021
SP - 275
EP - 278
DO - 10.5220/0010252002750278
PB - SciTePress