Automatic age estimation is a challenging problem attracting attention of the computer vision and pattern recognition communities due to its many practical applications. Artificial neural networks, such as CNNs are a popular tool for tackling this problem, and several datasets which can be used for training models are available. Despite the fact that dogs are the most well studied species in animal science, and that ageing processes in dogs are in many aspects similar to those of humans, the problem of age estimation for dogs has so far been overlooked. In this paper we present the DogAge dataset and an associated challenge, hoping to spark the interest of the scientific community in the yet unexplored problem of automatic dog age estimation.
|Title of host publication||Artificial Neural Networks and Machine Learning – ICANN 2019|
|Subtitle of host publication||Image Processing - 28th International Conference on Artificial Neural Networks, 2019, Proceedings|
|Editors||Igor V. Tetko, Pavel Karpov, Fabian Theis, Vera Kurková|
|Number of pages||6|
|State||Published - 2019|
|Event||28th International Conference on Artificial Neural Networks, ICANN 2019 - Munich, Germany|
Duration: 17 Sep 2019 → 19 Sep 2019
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||28th International Conference on Artificial Neural Networks, ICANN 2019|
|Period||17/09/19 → 19/09/19|
Bibliographical noteFunding Information:
This work has been supported by the NVIDIA GPU grant program.
© Springer Nature Switzerland AG 2019.
- Age estimation
- Applications of deep learning
- Computer vision
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science (all)