Vision-language models in remote sensing: Current progress and future trends
The remarkable achievements of ChatGPT and Generative Pre-trained Transformer 4 (GPT-
4) have sparked a wave of interest and research in the field of large language models …
4) have sparked a wave of interest and research in the field of large language models …
Remote sensing object detection in the deep learning era—a review
Given the large volume of remote sensing images collected daily, automatic object detection
and segmentation have been a consistent need in Earth observation (EO). However, objects …
and segmentation have been a consistent need in Earth observation (EO). However, objects …
Attention, please! A survey of neural attention models in deep learning
A de Santana Correia, EL Colombini - Artificial Intelligence Review, 2022 - Springer
In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …
limited ability to process competing sources, attention mechanisms select, modulate, and …
Hyperspectral image classification based on 3-D octave convolution with spatial–spectral attention network
In recent years, with the development of deep learning (DL), the hyperspectral image (HSI)
classification methods based on DL have shown superior performance. Although these DL …
classification methods based on DL have shown superior performance. Although these DL …
RSVQA: Visual question answering for remote sensing data
This article introduces the task of visual question answering for remote sensing data
(RSVQA). Remote sensing images contain a wealth of information, which can be useful for a …
(RSVQA). Remote sensing images contain a wealth of information, which can be useful for a …
Rsgpt: A remote sensing vision language model and benchmark
The emergence of large-scale large language models, with GPT-4 as a prominent example,
has significantly propelled the rapid advancement of artificial general intelligence and …
has significantly propelled the rapid advancement of artificial general intelligence and …
NWPU-captions dataset and MLCA-net for remote sensing image captioning
Q Cheng, H Huang, Y Xu, Y Zhou, H Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recently, the burgeoning demands for captioning-related applications have inspired great
endeavors in the remote sensing community. However, current benchmark datasets are …
endeavors in the remote sensing community. However, current benchmark datasets are …
A decoupling paradigm with prompt learning for remote sensing image change captioning
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 …
differences between bitemporal images by natural language. Previous methods ignore a …
Word–sentence framework for remote sensing image captioning
Remote sensing image captioning (RSIC), which aims at generating a well-formed sentence
for a remote sensing image, has attracted more attention in recent years. The general …
for a remote sensing image, has attracted more attention in recent years. The general …
Truncation cross entropy loss for remote sensing image captioning
Recently, remote sensing image captioning (RSIC) has drawn an increasing attention. In this
field, the encoder-decoder-based methods have become the mainstream due to their …
field, the encoder-decoder-based methods have become the mainstream due to their …