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pro vyhledávání: '"Parameswaran, Sethupathy"'
Methods proposed in the literature for zero-shot learning (ZSL) are typically suitable for offline learning and cannot continually learn from sequential streaming data. The sequential data comes in the form of tasks during training. Recently, a few a
Externí odkaz:
http://arxiv.org/abs/2103.10741
Zero-shot learning is a new paradigm to classify objects from classes that are not available at training time. Zero-shot learning (ZSL) methods have attracted considerable attention in recent years because of their ability to classify unseen/novel cl
Externí odkaz:
http://arxiv.org/abs/2101.08894
Recently, zero-shot learning (ZSL) emerged as an exciting topic and attracted a lot of attention. ZSL aims to classify unseen classes by transferring the knowledge from seen classes to unseen classes based on the class description. Despite showing pr
Externí odkaz:
http://arxiv.org/abs/2011.08508
Publikováno v:
In Neural Networks November 2022 155:487-497
Autor:
Parameswaran, Sethupathy, Rajaguru., Kaushik Ramana, Gopi, Saroj Harikrishnan, Ramakrishnananda, Balajee, Kumar Thangeswaran, Rajesh Senthil
Publikováno v:
AIP Conference Proceedings; 2019, Vol. 2134 Issue 1, p020005-1-020005-5, 5p, 3 Graphs