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Towards Learning Object Detectors with Limited Data for Industrial Applications

By Karim Guirguis

Towards Learning Object Detectors with Limited Data for Industrial Applications

By Karim Guirguis

- Default Title
Description
In dieser Dissertation werden drei neuartige Generalized FSOD (G-FSOD)-Ansätze vorgestellt, die das Vergessen von zuvor gelernten Klassen beim Lernen neuer Klassen mit begrenzten Daten minimieren. Die ersten beiden Ansätze reduzieren das Vergessen von Basisklassen, wenn diese während des Trainings noch verfügbar sind. Der dritte Ansatz, für Szenarien ohne Basisdaten, nutzt Wissensdestillation, um den Wissenstransfer zu verbessern. In this dissertation, three novel Generalized Few-Shot Object Detection (G-FSOD) approaches are presented to minimize the forgetting of previously learned classes while learning new classes with limited data. The first two approaches reduce the forgetting of base classes if they are still available during training. The third approach, for scenarios without base data, uses knowledge distillation to improve the knowledge transfer.
Product details
Binding:
Paperback
Edition:
1
Number of Pages:
264
Release Date:
2025-04-02
Publication Date:
2025-04-02
Publisher:
Karlsruher Institut für Technologie
Languages:
Original: English
ISBN10:
3731513897
ISBN13:
9783731513896
GPSR Manufacturer Reference:
[email protected]
Weight:
387 g
Height:
148 cm
Width:
210 cm
Thickness:
17 cm
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