TY - GEN
T1 - Multi-scale cropping mechanism for remote sensing image captioning
AU - Zhang, Xueting
AU - Wang, Qi
AU - Chen, Shangdong
AU - Li, Xuelong
N1 - Publisher Copyright:
©2019 IEEE
PY - 2019
Y1 - 2019
N2 - With the rapid development of artificial satellite, a large number of high resolution remote sensing images can be easily obtained now. Recently, remote sensing image captioning, which aims to generate accurate and concise descriptive sentences for remote sensing images, has been promoted by template-based model and encoder-decoder model with several related datasets released. Based on an encoder-decoder model, we propose a training mechanism of multi-scale cropping for remote sensing image captioning in this paper, which can extract more fine-grained information from remote sensing images and enhance the generalization performance of the base model. The experimental results on two datasets UCM-captions and Sydney-captions demonstrate that the proposed approach availably improves the performances in describing high resolution remote sensing images.
AB - With the rapid development of artificial satellite, a large number of high resolution remote sensing images can be easily obtained now. Recently, remote sensing image captioning, which aims to generate accurate and concise descriptive sentences for remote sensing images, has been promoted by template-based model and encoder-decoder model with several related datasets released. Based on an encoder-decoder model, we propose a training mechanism of multi-scale cropping for remote sensing image captioning in this paper, which can extract more fine-grained information from remote sensing images and enhance the generalization performance of the base model. The experimental results on two datasets UCM-captions and Sydney-captions demonstrate that the proposed approach availably improves the performances in describing high resolution remote sensing images.
KW - Encoder-decoder
KW - Image captioning
KW - Multi-scale cropping
KW - Remote sensing image
UR - https://www.scopus.com/pages/publications/85072538630
U2 - 10.1109/IGARSS.2019.8900503
DO - 10.1109/IGARSS.2019.8900503
M3 - 会议稿件
AN - SCOPUS:85072538630
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 10039
EP - 10042
BT - 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Y2 - 28 July 2019 through 2 August 2019
ER -