Age estimation using soft labelling ordinal classification approaches
V. Vargas, A. Gómez-Orellana, D. Guijo-Rubio, F. Bérchez-Moreno, P. Gutiérrez, C. Hervás-Martínez
Conference of the spanish association for artificial intelligence, pp. 1-10, 2024Abstract
This work explores the use of diverse soft labelling approaches recently proposed in the literature to address four distinct problems in age estimation. This kind of challenge can be considered an ordinal classification problem in machine learning or deep learning areas, as it exhibits a natural order among categories, reflecting the underlying age ranges defining each category. Soft labelling represents a machine learning approach in which, instead of assigning a single label to each instance in the dataset, a probability distribution across a range of labels is allocated. Soft labelling approaches prove particularly effective for age estimation due to the inherent uncertainty and continuity in age progression, which makes accurate age estimation from physical appearance difficult. Unlike categorical labels, age is a continuous variable that evolves over time. Thus, unlike hard labelling, soft labelling more effectively acknowledges the continuity and uncertainty inherent in age estimation. The experiments conducted in this study facilitate the comparison of soft labelling approaches against the nominal baseline. Results demonstrate superior performance of soft labelling approaches. Moreover, the statistical analysis reveals that use of a beta distribution to define soft labels yields the best results.
Cite this publication
BibTex
@inproceedings{vargas2024age,
author = {Víctor Manuel Vargas and Antonio Manuel Gómez-Orellana and David Guijo-Rubio and Francisco Bérchez-Moreno and Pedro Antonio Gutiérrez and César Hervás-Martínez},
title = {Age estimation using soft labelling ordinal classification approaches},
booktitle = {Conference of the spanish association for artificial intelligence},
year = {2024},
pages = {1--10},
doi = {10.1007/978-3-031-62799-6_5}
}
APA
Vargas, V., Gómez-Orellana, A., Guijo-Rubio, D., Bérchez-Moreno, F., Gutiérrez, P., Hervás-Martínez, C. (2024). Age estimation using soft labelling ordinal classification approaches. In Conference of the spanish association for artificial intelligence (pp. 1-10).
CV
V.M. Vargas, A.M. Gómez-Orellana, D. Guijo-Rubio, F. Bérchez-Moreno, P.A. Gutiérrez, C. Hervás-Martínez, (1/6) "Age estimation using soft labelling ordinal classification approaches". Conference of the spanish association for artificial intelligence, pp. 1-10, 2024.
RIS
TY - CONF T1 - Age estimation using soft labelling ordinal classification approaches T2 - Conference of the spanish association for artificial intelligence AU - Vargas, Víctor Manuel AU - Gómez-Orellana, Antonio Manuel AU - Guijo-Rubio, David AU - Bérchez-Moreno, Francisco AU - Gutiérrez, Pedro Antonio AU - Hervás-Martínez, César JO - Conference of the spanish association for artificial intelligence JA - Conference of the spanish association for artificial intelligence Y1 - 2024 PY - 2024 SP - 1 EP - 10 DO - 10.1007/978-3-031-62799-6_5 ER -