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Heterogeneity-Stratified Bootstrap Oversampling for Training a Spoiled Food Detector

Kunz, Pertami J. ; Zoubir, Abdelhak M. (2023)
Heterogeneity-Stratified Bootstrap Oversampling for Training a Spoiled Food Detector.
2023 24th International Conference on Digital Signal Processing. Rhodes, Greece (11.06.2023-13.06.2023)
doi: 10.1109/DSP58604.2023.10167943
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

We propose the Heterogeneity-Stratified Bootstrap (HSBoot), a stratification method that gives higher resampling probabilities to the sample points in the less homogeneous regions. We demonstrate its advantage in the case of training a detector by oversampling the under-represented class in an imbalanced data set. We took a case study of a spoiled food detector in form of an electronic nose. The performance metrics were calculated on the out-of-bag test set as well as on measurements collected from another sensor.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2023
Autor(en): Kunz, Pertami J. ; Zoubir, Abdelhak M.
Art des Eintrags: Bibliographie
Titel: Heterogeneity-Stratified Bootstrap Oversampling for Training a Spoiled Food Detector
Sprache: Englisch
Publikationsjahr: 5 Juli 2023
Verlag: IEEE
Buchtitel: 24th DSP 2023: 2023 24th International Conference on Digital Signal Processing
Veranstaltungstitel: 2023 24th International Conference on Digital Signal Processing
Veranstaltungsort: Rhodes, Greece
Veranstaltungsdatum: 11.06.2023-13.06.2023
DOI: 10.1109/DSP58604.2023.10167943
Kurzbeschreibung (Abstract):

We propose the Heterogeneity-Stratified Bootstrap (HSBoot), a stratification method that gives higher resampling probabilities to the sample points in the less homogeneous regions. We demonstrate its advantage in the case of training a detector by oversampling the under-represented class in an imbalanced data set. We took a case study of a spoiled food detector in form of an electronic nose. The performance metrics were calculated on the out-of-bag test set as well as on measurements collected from another sensor.

Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Signalverarbeitung
Exzellenzinitiative
Exzellenzinitiative > Graduiertenschulen
Exzellenzinitiative > Graduiertenschulen > Graduate School of Computational Engineering (CE)
Hinterlegungsdatum: 10 Jul 2023 10:21
Letzte Änderung: 10 Jul 2023 10:21
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