A study of self-training variants for semi-supervised image classification (Q112381963): Preview

A study of self-training variants for semi-supervised image classification (Q112381963)
2021 doctoral thesis by Attaullah Sahito at University of Waikato

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Current Data About A study of self-training variants for semi-supervised image classification

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(Q187685)

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(Q112381117)

(P1932)	Sahito, Attaullah

(P123)

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+2021-00-00T00:00:00Z

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(P854)	https://hdl.handle.net/10289/14678

(Q11660)

(P1932)	Artificial intelligence

(P854)	https://hdl.handle.net/10289/14678

(Q6027324)

(P1932)	Transfer Learning

(P854)	https://hdl.handle.net/10289/14678

(Q192776)

(P1932)	Neural networks (Computer science)

(P854)	https://hdl.handle.net/10289/14678

(Q327008)

(P1932)	Image processing

(P854)	https://hdl.handle.net/10289/14678

(Q2539)

(P1932)	Machine learning

(P854)	https://hdl.handle.net/10289/14678

(Q77562367)

(P1932)	Self-supervised Learning

(P854)	https://hdl.handle.net/10289/14678

(Q1041418)

(P1932)	Semi-supervised Learning

(P854)	https://hdl.handle.net/10289/14678

(P953)

https://researchcommons.waikato.ac.nz/handle/10289/14678

(P1476)

"A study of self-training variants for semi-supervised image classification" (language: en)

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(Q118646558)

(Q57029685)

other details

description	2021 doctoral thesis by Attaullah Sahito at University of Waikato

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(P1184)	10289/14678