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  UniCon: Boosting Few-Shot Class Incremental Learning through Uniform Target Space and Contrastive Learning

Ahmed, N. (2023). UniCon: Boosting Few-Shot Class Incremental Learning through Uniform Target Space and Contrastive Learning. Master Thesis, Universität des Saarlandes, Saarbrücken.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000F-21EB-3 Version Permalink: https://hdl.handle.net/21.11116/0000-000F-21EC-2
Genre: Thesis

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Master Thesis Noor Ahmed.pdf (Any fulltext), 8MB
 
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Master Thesis Noor Ahmed.pdf
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 Creators:
Ahmed, Noor1, Author           
Kukleva, Anna1, Advisor           
Schiele, Bernt1, Referee                 
Ilg, Eddy2, Referee
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1Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society, ou_1116547              
2External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 20232023
 Publication Status: Issued
 Pages: 56 p.
 Publishing info: Saarbrücken : Universität des Saarlandes
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: AhmedMSc23
 Degree: Master

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