Improving Crowdsourcing-Based Image Classification Through Expanded Input Elicitation and Machine Learning

This work investigates how different forms of input elicitation obtained from crowdsourcing can be utilized to improve the quality of inferred labels for image classification tasks, where an image must be labeled as either positive or negative depending on the presence/absence of a specified object....

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Detalles Bibliográficos
Autores principales: Yasmin, Romena, Hassan, Md Mahmudulla, Grassel, Joshua T., Bhogaraju, Harika, Escobedo, Adolfo R., Fuentes, Olac
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9276979/
https://www.ncbi.nlm.nih.gov/pubmed/35845435
http://dx.doi.org/10.3389/frai.2022.848056

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9276979/
https://www.ncbi.nlm.nih.gov/pubmed/35845435
http://dx.doi.org/10.3389/frai.2022.848056

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