A Human-In-One-Loop Active Domain Adaptation Framework for Digit Recognition

IF 2.9 4区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Applied Artificial Intelligence Pub Date : 2024-05-11 DOI:10.1080/08839514.2024.2349410

Hao Xiu, Guanchen Li, Jie He, Xiaotong Zhang, Yue Qi

引用次数: 0

Abstract

Domain adaptation can effectively enhance a model’s performance on target domain data with limited data. However, when some target domain labels are obtainable, training the model with both source ...

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用于数字识别的人一环主动域适应框架

域适应可以在数据有限的情况下有效提高模型在目标域数据上的性能。然而，当可以获得一些目标域标签时，同时使用源数据和目标域数据训练模型的效果并不理想。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Artificial Intelligence 工程技术-工程：电子与电气

CiteScore

5.20

自引率

3.60%

发文量

106

审稿时长

6 months

期刊介绍： Applied Artificial Intelligence addresses concerns in applied research and applications of artificial intelligence (AI). The journal also acts as a medium for exchanging ideas and thoughts about impacts of AI research. Articles highlight advances in uses of AI systems for solving tasks in management, industry, engineering, administration, and education; evaluations of existing AI systems and tools, emphasizing comparative studies and user experiences; and the economic, social, and cultural impacts of AI. Papers on key applications, highlighting methods, time schedules, person-months needed, and other relevant material are welcome.