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Computational, label, and data efficiency in deep learning for sparse 3D data / by Lanxiao Li

By: Resource type: Ressourcentyp: BuchBookLanguage: English Series: Karlsruher Institut für Technologie. Forschungsberichte aus der industriellen Informationstechnik ; Band 33Publisher: Karlsruhe : KIT Scientific Publishing, [2024]Description: xiii, 227 Seiten : IllustrationenISBN:
  • 9783731513469
Subject(s): Genre/Form: Additional physical formats: No title | Erscheint auch als: Computational, label, and data efficiency in deep learning for sparse 3D data. Online-Ausgabe Karlsruhe : KIT Scientific Publishing, 2024. 1 Online-Ressource (xiii, 227 Seiten)DDC classification:
  • 621.3
Action note:
  • Archivierung/Langzeitarchivierung gewährleistet DISS
Dissertation note: Dissertation - Karlsruher Institut für Technologie (KIT), 2023 Summary: Deep learning is widely applied to sparse 3D data to perform challenging tasks, e.g., 3D object detection and semantic segmentation. However, the high performance of deep learning comes with high costs, including computational costs and the effort to capture and label data. This work investigates and improves the efficiency of deep learning for sparse 3D data to overcome the obstacles to the further development of this technologyCall number: Grundsignatur: 2024 A 412PPN: PPN: 1888290609
Holdings
Item type Home library Collection Shelving location Call number Status Barcode Item holds
Magazinbestand ausleihbar Bibliothek Campus Süd elt 11 Geschlossenes Magazin 2024 A 412 On hold 53791552090 1
Institutsbestand IIIT Institutsbibliothek Y160 Not for loan
Total holds: 1

Archivierung/Langzeitarchivierung gewährleistet DISS pdager DE-90

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