Computational, Label, and Data Efficiency in Deep Learning for Sparse 3D Data
(Sprache: Englisch)
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...
Voraussichtlich lieferbar in 3 Tag(en)
versandkostenfrei
Buch (Kartoniert)
Fr. 52.90
inkl. MwSt.
- Kreditkarte, Paypal, Rechnungskauf
- 30 Tage Widerrufsrecht
Produktdetails
Produktinformationen zu „Computational, Label, and Data Efficiency in Deep Learning for Sparse 3D Data “
Klappentext zu „Computational, Label, and Data Efficiency in Deep Learning for Sparse 3D Data “
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 technology.
Bibliographische Angaben
- Autor: Lanxiao Li
- 2024, 256 Seiten, Masse: 14,8 x 21 cm, Kartoniert (TB), Englisch
- Verlag: KIT Scientific Publishing
- ISBN-10: 3731513463
- ISBN-13: 9783731513469
Sprache:
Englisch
Kommentar zu "Computational, Label, and Data Efficiency in Deep Learning for Sparse 3D Data"
0 Gebrauchte Artikel zu „Computational, Label, and Data Efficiency in Deep Learning for Sparse 3D Data“
| Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
|---|
Schreiben Sie einen Kommentar zu "Computational, Label, and Data Efficiency in Deep Learning for Sparse 3D Data".
Kommentar verfassen