MLRSNet: A multi-label high spatial resolution remote sensing dataset for semantic scene understanding

• Published in: ISPRS journal of photogrammetry and remote sensing Vol. 169; pp. 337 - 350
• Main Authors: Qi, Xiaoman, Zhu, Panpan, Wang, Yuebin, Zhang, Liqiang, Peng, Junhuan, Wu, Mengfan, Chen, Jialong, Zhao, Xudong, Zang, Ning, Mathiopoulos, P. Takis
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.11.2020
• Subjects: Convolutional Neural Network (CNN); data collection; image analysis; Image classification; Image retrieval; land cover; Multi-label image dataset; photogrammetry; satellites; Semantic scene understanding; visual perception; Semantic scene understanding; Multi-label image dataset; Image retrieval; Convolutional Neural Network (CNN); Image classification

To better understand scene images in the field of remote sensing, multi-label annotation of scene images is necessary. Moreover, to enhance the performance of deep learning models for dealing with semantic scene understanding tasks, it is vital to train them on large-scale annotated data. However, m...