Active-Learning
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资源简介
Active Learning for Instance-Aware Object Detection (AIFT), as presented in CVPR 2017, proposes a novel framework for object detection that leverages active learning principles. The official implementation of AIFT provides a comprehensive solution for training instance-aware object detectors in a semi-supervised manner. It involves strategies for selecting informative samples from an unlabeled dataset to actively query annotations, thus optimizing model performance with minimal labeled data. By iteratively refining the model through active learning, AIFT effectively addresses the challenge of limited annotated data, leading to improved object detection accuracy and efficiency.
- 资源类型
- 软件
- 第三方域名
- github.com
- 索引时间
- 2026-08-04 01:10
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