通过最优运输的视角研究视觉特征偏差

IF 2.8 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Data Mining and Knowledge Discovery Pub Date : 2023-09-02 DOI:10.1007/s10618-023-00972-2

Simone Fabbrizzi, Xuan Zhao, Emmanouil Krasanakis, Symeon Papadopoulos, Eirini Ntoutsi

引用次数: 1

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Studying bias in visual features through the lens of optimal transport

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Studying bias in visual features through the lens of optimal transport

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来源期刊

Data Mining and Knowledge Discovery 工程技术-计算机：人工智能

CiteScore

10.40

自引率

4.20%

发文量

审稿时长

10 months

期刊介绍： Advances in data gathering, storage, and distribution have created a need for computational tools and techniques to aid in data analysis. Data Mining and Knowledge Discovery in Databases (KDD) is a rapidly growing area of research and application that builds on techniques and theories from many fields, including statistics, databases, pattern recognition and learning, data visualization, uncertainty modelling, data warehousing and OLAP, optimization, and high performance computing.