Image captioning is a pretty modern area of the convergence of computer vision and natural
language processing and is widely used in a range of applications such as multi-modal …

Analyzing land cover changes with multitemporal remote sensing (RS) images is crucial for
environmental protection and land planning. In this article, we explore RS image change …

Automatically generating language descriptions of remote sensing images has become an
emerging research hot spot in the remote sensing field. Attention-based captioning, as a …

Recently, the burgeoning demands for captioning-related applications have inspired great
endeavors in the remote sensing community. However, current benchmark datasets are …

Remote sensing image change captioning (RSICC) is a novel task that aims to describe the
differences between bitemporal images by natural language. Previous methods ignore a …

Recently, vision-language models based on transformers are gaining popularity for joint
modeling of visual and textual modalities. In particular, they show impressive results when …

The emerging field of vision–language models, which combines computer vision and natural
language processing (NLP), has gained significant interest and exploration. This integration …

The encoder–decoder framework is prevalent in existing remote-sensing image captioning
(RSIC) models. The appearance of attention mechanisms brings significant results …

Most of the remote sensing image captioning (IC) models are based on encoder–decoder
frameworks where a convolutional neural network (CNN) encodes the image information …

Remote-sensing image (RSI) captioning aims to automatically generate sentences
describing the content of RSIs. The multiscale information of RSIs contains attributes and …