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Authors: Muhammad Asif Khan 1 ; Hamid Menouar 1 and Ridha Hamila 2

Affiliations: 1 Qatar Mobility Innovations Center, Qatar University, Doha, Qatar ; 2 Department of Electrical Engineering, Qatar University, Doha, Qatar

Keyword(s): Crowd Counting, Curriculum Learning, CNN, Density Estimation.

Abstract: Recent advances in deep learning techniques have achieved remarkable performance in several computer vision problems. A notably intuitive technique called Curriculum Learning (CL) has been introduced recently for training deep learning models. Surprisingly, curriculum learning achieves significantly improved results in some tasks but marginal or no improvement in others. Hence, there is still a debate about its adoption as a standard method to train supervised learning models. In this work, we investigate the impact of curriculum learning in crowd counting using the density estimation method. We performed detailed investigations by conducting 112 experiments using six different CL settings using eight different crowd models. Our experiments show that curriculum learning improves the model learning performance and shortens the convergence time.

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Paper citation in several formats:
Khan, M. A., Menouar, H. and Hamila, R. (2024). Curriculum for Crowd Counting: Is It Worthy?. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-679-8; ISSN 2184-4321, SciTePress, pages 583-590. DOI: 10.5220/0012414700003660

@conference{visapp24,
author={Muhammad Asif Khan and Hamid Menouar and Ridha Hamila},
title={Curriculum for Crowd Counting: Is It Worthy?},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2024},
pages={583-590},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012414700003660},
isbn={978-989-758-679-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Curriculum for Crowd Counting: Is It Worthy?
SN - 978-989-758-679-8
IS - 2184-4321
AU - Khan, M.
AU - Menouar, H.
AU - Hamila, R.
PY - 2024
SP - 583
EP - 590
DO - 10.5220/0012414700003660
PB - SciTePress

- Science and Technology Publications, Lda.
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