Dynamic-budget superpixel active learning for semantic segmentation

The presented dynamic-budget querying strategy is simple, effective, and can be easily adapted to other regional active learning algorithms to further improve the data efficiency of semantic segmentation tasks.

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Publication Details

Journal
Frontiers in Artificial Intelligence
Published
2025-01-09
DOI
https://doi.org/10.3389/frai.2024.1498956
Citations
1
Primary Topic
Sparse and Compressive Sensing Techniques
Type
article
Field-Weighted Citation Impact
1.33

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article

Dynamic-budget superpixel active learning for semantic segmentation

Ian Stavness, Yuemin Wang
1 citations
Frontiers in Artificial Intelligence
Sparse and Compressive Sensing Techniques
1.33
article

Dynamic-budget superpixel active learning for semantic segmentation

Ian Stavness, Yuemin Wang
article en
1 citations

Abstract

The presented dynamic-budget querying strategy is simple, effective, and can be easily adapted to other regional active learning algorithms to further improve the data efficiency of semantic segmentation tasks.

Frontiers in Artificial IntelligenceVol. 7
University of Saskatchewan (CA)
Canada First Research Excellence Fund
Openalex Percentile: Top 28%
Sparse and Compressive Sensing Techniques
1.33
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Dynamic-budget superpixel active learning for semantic segmentation — Ian Stavness, Yuemin Wang · Frontiers in Artificial Intelligence (2025) | TGRS Research Map | TGRS