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  • 标题:Visual Cultural Biases in Food Classification
  • 本地全文:下载
  • 作者:Qing Zhang ; David Elsweiler ; Christoph Trattner
  • 期刊名称:Foods
  • 电子版ISSN:2304-8158
  • 出版年度:2020
  • 卷号:9
  • 期号:6
  • 页码:823-844
  • DOI:10.3390/foods9060823
  • 出版社:MDPI Publishing
  • 摘要:This article investigates how visual biases influence the choices made by people and machines in the context of online food. To this end the paper investigates three research questions and shows (i) to what extent machines are able to classify images, (ii) how this compares to human performance on the same task and (iii) which factors are involved in the decision making of both humans and machines. The research reveals that algorithms significantly outperform human labellers on this task with a range of biases being present in the decision-making process. The results are important as they have a range of implications for research, such as recommender technology and crowdsourcing, as is discussed in the article.
  • 关键词:visual biases; food classification; crowdsourcing visual biases ; food classification ; crowdsourcing
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