Adaptive Remote Sensing Image Attribute Learning for Active Object
Detection
- URL: http://arxiv.org/abs/2101.06438v1
- Date: Sat, 16 Jan 2021 11:37:50 GMT
- Title: Adaptive Remote Sensing Image Attribute Learning for Active Object
Detection
- Authors: Nuo Xu, Chunlei Huo, Jiacheng Guo, Yiwei Liu, Jian Wang and Chunhong
Pan
- Abstract summary: This paper takes adaptive brightness adjustment and scale adjustment as examples, and proposes an active object detection method based on deep reinforcement learning.
The goal of adaptive image attribute learning is to maximize the detection performance.
- Score: 43.029857143916345
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: In recent years, deep learning methods bring incredible progress to the field
of object detection. However, in the field of remote sensing image processing,
existing methods neglect the relationship between imaging configuration and
detection performance, and do not take into account the importance of detection
performance feedback for improving image quality. Therefore, detection
performance is limited by the passive nature of the conventional object
detection framework. In order to solve the above limitations, this paper takes
adaptive brightness adjustment and scale adjustment as examples, and proposes
an active object detection method based on deep reinforcement learning. The
goal of adaptive image attribute learning is to maximize the detection
performance. With the help of active object detection and image attribute
adjustment strategies, low-quality images can be converted into high-quality
images, and the overall performance is improved without retraining the
detector.
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