Explainable machine learning for predicting the mechanical properties in bainitic steels

Autor: Marc Ackermann, Deniz Iren, Yao Yao

Publikováno v: Materials & Design, Vol 230, Iss , Pp 111946- (2023)

Microstructures in steel can be understood as hierarchical structures holding information on various length scales (e.g. from nano to macro scale). In electron microscopy images, the microscope resolution allows extraction of meso-scale information o

Externí odkaz: https://doaj.org/article/f95b183c925349f9af20b5b4b866b00b

Özel Eğitim Öğretmenlerinde Sabır ve İş Doyumu İlişkisi. (Turkish)

Autor: Erdem, Mustafa, Meriç, Erdal, Bayat, Deniz İren

Publikováno v: Buca Faculty of Education Journal / Buca Egitim Fakültesi Dergisi; mar2024, Issue 59, p27-50, 24p

Interpretable Explainability in Facial Emotion Recognition and Gamification for Data Collection

Autor: Krist Shingjergji, Deniz Iren, Felix Bottger, Corrie Urlings, Roland Klemke

Publikováno v: Shingjergi, K, Iren, Y D, Klemke, R, Urlings, C C J & Böttger, F 2022, Interpretable Explainability in Facial Emotion Recognition and Gamification for Data Collection . in 2022 10th International Conference on Affective Computing and Intelligent Interaction, ACII 2022 . IEEE, 10th International Conference on Affective Computing and Intelligent Interaction, Nara, Japan, 18/10/22 . https://doi.org/10.1109/ACII55700.2022.9953864
IEEE Affective Computing and Intelligent Interaction

Training facial emotion recognition models requires large sets of data and costly annotation processes. To alleviate this problem, we developed a gamified method of acquiring annotated facial emotion data without an explicit labeling effort by humans

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4457eec0f3ae3f46c5aaafb0a14cf40e
https://research.ou.nl/en/publications/4b5a2b16-947d-4361-86a0-de2a004f9356

Using AI to predict service agent stress from emotion patterns in service interactions

Autor: Deniz Iren, Stefano Bromuri, Alexander P. Henkel, Visara Urovi

Publikováno v: Bromuri, S, Henkel, A P, Iren, D & Urovi, V 2021, ' Using AI to predict service agent stress from emotion patterns in service interactions ', Journal of Service Management, vol. 32, no. 4, pp. 581-611 . https://doi.org/10.1108/josm-06-2019-0163
Journal of Service Management, 32(4), 581-611. Emerald Group Publishing Ltd.

PurposeA vast body of literature has documented the negative consequences of stress on employee performance and well-being. These deleterious effects are particularly pronounced for service agents who need to constantly endure and manage customer emo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7580c3529f25c8dedadc50b3c555f844
https://doi.org/10.1108/josm-06-2019-0163

Identification and analysis of handovers in organisations using process model repositories

Autor: Deniz Iren, Michael Leyer, Banu Aysolmaz

Publikováno v: Leyer, M, Iren, D & Aysolmaz, B 2020, ' Identification and analysis of handovers in organisations using process model repositories ', Business Process Management Journal, vol. 26, no. 6, pp. 1599-1617 . https://doi.org/10.1108/BPMJ-01-2019-0041
Business Process Management Journal, 26(6), 1599-1617. Emerald Group Publishing Ltd.

PurposeIdentifying handovers is an important but difficult to achieve goal for companies as handovers have advantages allowing for specialisation in processes as well as disadvantages by creating erroneous interfaces.Design/methodology/approachConcep

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f0cad1d1ba2d69cc0ef24d4427c3837
https://doi.org/10.1108/bpmj-01-2019-0041