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Incremental zero-shot learning based on attributes for image classification

2017 IEEE International Conference on Image Processing (ICIP), 2017
Instead of assuming a closed-world environment comprising a fixed number of objects, modern pattern recognition systems need to recognize outliers, identify anomalies, or discover entirely new objects, which is known as zero-shot object recognition.
Nan Xue 0004   +3 more
openaire   +1 more source

Enhanced VAEGAN: a zero-shot image classification method

Applied Intelligence, 2022
Bo Ding 0003   +3 more
openaire   +2 more sources

Boosting Zero-Shot Image Classification via Pairwise Relationship Learning

2017
Zero-shot image classification (ZSIC) is one of the emerging challenges in the communities of computer vision, artificial intelligence and machine learning. In this paper, we propose to exploit the pairwise relationships between test instances to increase the performance of conventional methods, e.g.
Hanhui Li   +5 more
openaire   +2 more sources

Towards Zero-Shot Document Image Classification

2025 38th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)
Lucas Macedo   +4 more
openaire   +1 more source

Self-Supervised Generalized Zero Shot Learning for Medical Image Classification Using Novel Interpretable Saliency Maps

IEEE Transactions on Medical Imaging, 2022
Dwarikanath Mahapatra   +2 more
exaly  

Attribute-Guided Zero-Shot CLIP in Image Classification

2025 IEEE International Conference on Multimedia and Expo (ICME)
Guoxi Qiu   +3 more
openaire   +2 more sources

Generalized Zero-Shot Recognition Through Image-Guided Semantic Classification

2021 IEEE International Conference on Image Processing (ICIP), 2021
Fang Li, Mei-Chen Yeh
openaire   +2 more sources

A Review of Zero-Shot Image Classification

Huadong Sun   +3 more
openaire   +1 more source

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