Correction: Martin et al. ApeTI: A Thermal Image Dataset for Face and Nose Segmentation with Apes. Signals 2024, 5, 147–164
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- 25. Martin, P.-E.; Kachel, G.; Wieg, N.; Eckert, J.; Haun, D.B.M. ApeTI Dataset and Models Weights [Data Set]. Zenodo. 2024. Available online: https://doi.org/10.5281/zenodo.11192141 (accessed on 20 May 2024).
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- 26. Martin, P.-E. Ccp-eva/ApeTI: Software (v1.0.0). Zenodo. 2024. Available online: https://doi.org/10.5281/zenodo.11204561 (accessed on 20 May 2024).
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- The Introduction, which should read as follows: “In this paper, we present the acquired Ape Thermal Image dataset (ApeTI) and our methods to detect chimpanzees’ face and nose landmarks from thermal images. The dataset is available online [25,26] (https://doi.org/10.5281/zenodo.11192141 (accessed on 20 May 2024)). Different methods are compared and combined on both tasks using the mean average precision (mAP) metrics. Section 2 introduces the ApeTI dataset and the evaluation procedure. We then present the different tested methods and their results, respectively, in Section 3 and Section 4. Subsequently, we outline the project’s scope, demonstrate a proof of concept for physiological signals retrieval, and discuss our future work in Section 5. We finally draw our conclusion in Section 6.”
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- ApeTI Dataset, the Evaluation Strategy subsection, which should read as follows: “The dataset is split videowise between train, validation, and test sets, meaning frames of the same video can be found only in one of the sets. The ground-truth annotations and the splits of the dataset are shared using the COCO format in our repository. This dataset allows for solving two tasks: chimpanzee face detection and nose landmark regression. We encourage researchers to use this dataset to benchmark their methods. Our model configurations, leaderboard, and guidelines for downloading the data are available on the dedicated GitHub repository [26] (https://github.com/ccp-eva/ApeTI) (accessed on 20 May 2024).”
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- The Data Availability Statement, which should read as follows: “We encourage researchers to use this dataset to benchmark their methods. Our model configurations, leaderboard, and guidelines for downloading the data are available on the dedicated GitHub repository [26]: https://github.com/ccp-eva/ApeTI (accessed on 20 May 2024). The data used for training and evaluating the different models mentioned in this paper and the weights of the Tifa and Tina models are available on the dedicated Zenodo repository [25]: https://doi.org/10.5281/zenodo.11192141 (accessed on 20 May 2024). The original recordings mentioned in this paper are available upon request by writing to the main author.”
Reference
- Martin, P.-E.; Kachel, G.; Wieg, N.; Eckert, J.; Haun, D.B.M. ApeTI: A Thermal Image Dataset for Face and Nose Segmentation with Apes. Signals 2024, 5, 147–164. [Google Scholar] [CrossRef]
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Martin, P.-E.; Kachel, G.; Wieg, N.; Eckert, J.; Haun, D.B.M. Correction: Martin et al. ApeTI: A Thermal Image Dataset for Face and Nose Segmentation with Apes. Signals 2024, 5, 147–164. Signals 2024, 5, 474-475. https://doi.org/10.3390/signals5030024
Martin P-E, Kachel G, Wieg N, Eckert J, Haun DBM. Correction: Martin et al. ApeTI: A Thermal Image Dataset for Face and Nose Segmentation with Apes. Signals 2024, 5, 147–164. Signals. 2024; 5(3):474-475. https://doi.org/10.3390/signals5030024
Chicago/Turabian StyleMartin, Pierre-Etienne, Gregor Kachel, Nicolas Wieg, Johanna Eckert, and Daniel B. M. Haun. 2024. "Correction: Martin et al. ApeTI: A Thermal Image Dataset for Face and Nose Segmentation with Apes. Signals 2024, 5, 147–164" Signals 5, no. 3: 474-475. https://doi.org/10.3390/signals5030024
APA StyleMartin, P. -E., Kachel, G., Wieg, N., Eckert, J., & Haun, D. B. M. (2024). Correction: Martin et al. ApeTI: A Thermal Image Dataset for Face and Nose Segmentation with Apes. Signals 2024, 5, 147–164. Signals, 5(3), 474-475. https://doi.org/10.3390/signals5030024