Learning from Imperfect Data Incremental Learning and Few-shot Learning

Liu, Yaoyao

doi:10.22028/D291-39511

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Learning from Imperfect Data Incremental Learning and Few-shot Learning

Liu, Y. (2023). Learning from Imperfect Data Incremental Learning and Few-shot Learning. PhD Thesis, Universität des Saarlandes, Saarbrücken. doi:10.22028/D291-39511.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-0392-A Version Permalink: https://hdl.handle.net/21.11116/0000-000F-6346-3

Genre: Thesis

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http://dx.doi.org/10.22028/D291-39511 (Any fulltext) Open Access Green

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Creators:
Liu, Yaoyao^{1, 2}, Author
Schiele, Bernt¹, Advisor
Tuytelaars, Tinne³, Referee
Tang, Siyu¹, Referee

Affiliations:
1Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society, ou_1116547
2International Max Planck Research School, MPI for Informatics, Max Planck Society, Campus E1 4, 66123 Saarbrücken, DE, ou_1116551
3External Organizations, ou_persistent22

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Language(s): eng - English

Dates: Accepted: 2023-01-27Published Online: 2023Date issued: 2023

Publication Status: Issued

Pages: xiv, 172 p

Publishing info: Saarbrücken : Universität des Saarlandes

Table of Contents: -

Rev. Type: -

Identifiers: BibTex Citekey: Liu_PhD2023
URN: urn:nbn:de:bsz:291--ds-395111
DOI: 10.22028/D291-39511
Other: hdl:20.500.11880/35715

Degree: PhD

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