A zero-shot learning boosting framework via concept-constrained clustering-Reference-Cited by-同舟云学术

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A zero-shot learning boosting framework via concept-constrained clustering

Published:2024-01 Issue: Volume:145 Page:109937
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Yue Qin,Cui Junbiao^ORCID,Bai Liang,Liang Jianqing,Liang Jiye

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Ministry of Science and Technology of the People's Republic of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference39 articles.

1. Zero-shot learning and its applications from autonomous vehicles to COVID-19 diagnosis: A review;Rezaei;Intell.-Based Med.,2020

2. Artificial intelligence-based robust hybrid algorithm design and implementation for real-time detection of plant diseases in agricultural environments;Yağ;Biology,2022

3. Self-supervised generalized zero shot learning for medical image classification using novel interpretable saliency maps;Mahapatra;IEEE Trans. Med. Imag.,2022

4. DeViSE: A deep visual-semantic embedding model;Frome,2013

5. Transductive multi-view zero-shot learning;Fu;IEEE Trans. Pattern Anal. Mach. Intell.,2015

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