Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Online learning with novelty detection in human-guided road tracking

Date

Authors

Zhou, Jun

Cheng , Li

Bischof, Walter F.

Publisher

Institute of Electrical and Electronics Engineers (IEEE Inc)

Abstract

Current image processing and pattern recognition algorithms are not robust enough to make automated remote sensing image interpretation feasible. For this reason, we need to develop image interpretation systems that rely on human guidance. In this paper,

Keywords

Keywords: E-learning; Feature extraction; Human computer interaction; Iterative methods; Online systems; Aerial images; Image interpretation; Novelty detection; Online learning; Road tracking; Tracking (position) Aerial images; Human-computer interaction (HCI); Image interpretation; Novelty detection; Online learning; Road tracking

URI

http://hdl.handle.net/1885/50534

Collections

ANU Research Publications

Source

IEEE Transactions on Geoscience and Remote Sensing

Type

Journal article

DOI

10.1109/TGRS.2007.900697

Restricted until

2037-12-31

Downloads

File

Description

01_Zhou_Online_learning_with_novelty_2007.pdf (1.19 MB)