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| Creators: | Dreher, Sarah and Gebele, Jens and Brune, Philipp |
|---|---|
| Title: | Applying Transfer Testing to Identify Annotation Discrepancies in Facial Emotion Data Sets |
| Item Type: | Conference or Workshop Item |
| Event Title: | (Proceedings of the) 9th International Conference Mobile, Secure, and Programmable Networking (MSPN) |
| Event Location: | Paris, France |
| Event Dates: | October 26–27, 2023 |
| Projects: | TTZ-GZ |
| Page Range: | pp. 157-174 |
| Date: | 2024 |
| Divisions: | Informationsmanagement |
| Abstract (ENG): | The field of Artificial Intelligence (AI) has a significant impact on the way computers and humans interact. The topic of (facial) emotion recognition has gained a lot of attention in recent years. Majority of research literature focuses on improvement of algorithms and Machine Learning (ML) models for single data sets. Despite the impressive results achieved, the impact of the (training) data quality with its potential biases and annotation discrepancies is often neglected. Therefore, this paper demonstrates an approach to detect and evaluate annotation label discrepancies between three separate (facial) emotion recognition databases by Transfer Testing with three ML architectures. The findings indicate Transfer Testing to be a new promising method to detect inconsistencies in data annotations of emotional states, implying label bias and/or ambiguity. Therefore, Transfer Testing is a method to verify the transferability of trained ML models. Such research is the foundation for developing more accurate AI-based emotion recognition systems, which are also robust in real-life scenarios. |
| Forthcoming: | No |
| Main areas or research: | Transformationmanagement |
| Language: | English |
| Uncontrolled Keywords: | Emotion Recognition ; Facial Expression Recognition ; Emotional Artificial Intelligence ; Transfer Testing ; Data Quality ; Transferability |
| Citation: | Dreher, Sarah and Gebele, Jens and Brune, Philipp (2024) Applying Transfer Testing to Identify Annotation Discrepancies in Facial Emotion Data Sets. In: (Proceedings of the) 9th International Conference Mobile, Secure, and Programmable Networking (MSPN), October 26–27, 2023, Paris, France, pp. 157-174. (Lecture Notes in Computer Science; 14482). ISBN 9783031524264 |
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Applying Transfer Testing to Identify Annotation Discrepancies in Facial Emotion Data Sets. (deposited 11 Feb 2025 08:41)
- Applying Transfer Testing to Identify Annotation Discrepancies in Facial Emotion Data Sets. (deposited 11 Mar 2025 08:24) [Currently Displayed]
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