Kunz, Pertami J. ; Abid, Syrine ben ; Zoubir, Abdelhak M. (2023)
The Heterogeneity-Intensified and Heterogeneity Ratio-Stratified Bootstrap (HiS- and HeRS-Boot) Oversampling to Boost a Detector Performance.
IEEE Sensors 2023. Vienna, Austria (29.10.-01.11.2023)
doi: 10.1109/SENSORS56945.2023.10324861
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
We investigated two variations of the previously proposed heterogeneity-stratified bootstrap (HSBoot) oversampling method, namely the improved Heterogeneity-Stratified (HiS-) and Heterogeneity Ratio-Stratified (HeRS-) Boot, for balancing a data set by assigning higher resampling probabilities to sample points in less homogeneous regions. Our study focused on two detection cases: spoiled food and allergen. Results demonstrate the effectiveness and generalizability of our method across different sensors, highlighting its potential for real-world applications and positive impact on daily life.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Kunz, Pertami J. ; Abid, Syrine ben ; Zoubir, Abdelhak M. |
| Art des Eintrags: | Bibliographie |
| Titel: | The Heterogeneity-Intensified and Heterogeneity Ratio-Stratified Bootstrap (HiS- and HeRS-Boot) Oversampling to Boost a Detector Performance |
| Sprache: | Englisch |
| Publikationsjahr: | 28 November 2023 |
| Verlag: | IEEE |
| Buchtitel: | IEEE Sencors 2023: Conference Proceedings |
| Veranstaltungstitel: | IEEE Sensors 2023 |
| Veranstaltungsort: | Vienna, Austria |
| Veranstaltungsdatum: | 29.10.-01.11.2023 |
| DOI: | 10.1109/SENSORS56945.2023.10324861 |
| Kurzbeschreibung (Abstract): | We investigated two variations of the previously proposed heterogeneity-stratified bootstrap (HSBoot) oversampling method, namely the improved Heterogeneity-Stratified (HiS-) and Heterogeneity Ratio-Stratified (HeRS-) Boot, for balancing a data set by assigning higher resampling probabilities to sample points in less homogeneous regions. Our study focused on two detection cases: spoiled food and allergen. Results demonstrate the effectiveness and generalizability of our method across different sensors, highlighting its potential for real-world applications and positive impact on daily life. |
| 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: | 18 Jan 2024 09:42 |
| Letzte Änderung: | 22 Feb 2024 08:34 |
| PPN: | 515727172 |
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