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Attributes’ Importance for Zero-Shot Pose-Classification Based on Wearable Sensors

This paper presents a simple yet effective method for improving the performance of zero-shot learning (ZSL). ZSL classifies instances of unseen classes, from which no training data is available, by utilizing the attributes of the classes. Conventional ZSL methods have equally dealt with all the avai...

Deskribapen osoa

Gorde:
Xehetasun bibliografikoak
Argitaratua izan da:Sensors (Basel)
Egile Nagusiak: Ohashi, Hiroki, Al-Naser, Mohammad, Ahmed, Sheraz, Nakamura, Katsuyuki, Sato, Takuto, Dengel, Andreas
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: MDPI 2018
Gaiak:
Sarrera elektronikoa:https://ncbi.nlm.nih.gov/pmc/articles/PMC6111934/
https://ncbi.nlm.nih.gov/pubmed/30071586
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s18082485
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