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Advances and challenges in deep learning-based change detection for remote sensing images: A review through various learning paradigms
Change detection (CD) in remote sensing (RS) imagery is a pivotal method for detecting
changes in the Earth's surface, finding wide applications in urban planning, disaster …
changes in the Earth's surface, finding wide applications in urban planning, disaster …
ChangeCLIP: Remote sensing change detection with multimodal vision-language representation learning
Remote sensing change detection (RSCD), which aims to identify surface changes from
bitemporal images, is significant for many applications, such as environmental protection …
bitemporal images, is significant for many applications, such as environmental protection …
Rs-llava: A large vision-language model for joint captioning and question answering in remote sensing imagery
Y Bazi, L Bashmal, MM Al Rahhal, R Ricci, F Melgani - Remote Sensing, 2024 - mdpi.com
In this paper, we delve into the innovative application of large language models (LLMs) and
their extension, large vision-language models (LVLMs), in the field of remote sensing (RS) …
their extension, large vision-language models (LVLMs), in the field of remote sensing (RS) …
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 …
Parameter-efficient transfer learning for remote sensing image–text retrieval
Vision-and-language pretraining (VLP) models have experienced a surge in popularity
recently. By fine-tuning them on specific datasets, significant performance improvements …
recently. By fine-tuning them on specific datasets, significant performance improvements …
Change-agent: Towards interactive comprehensive remote sensing change interpretation and analysis
Monitoring changes in the Earth's surface is crucial for understanding natural processes and
human impacts, necessitating precise and comprehensive interpretation methodologies …
human impacts, necessitating precise and comprehensive interpretation methodologies …
Changes to captions: An attentive network for remote sensing change captioning
In recent years, advanced research has focused on the direct learning and analysis of
remote-sensing images using natural language processing (NLP) techniques. The ability to …
remote-sensing images using natural language processing (NLP) techniques. The ability to …
Language Integration in Remote Sensing: Tasks, datasets, and future directions
The emerging field of vision–language models, which combines computer vision and natural
language processing (NLP), has gained significant interest and exploration. This integration …
language processing (NLP), has gained significant interest and exploration. This integration …
Rscama: Remote sensing image change captioning with state space model
Remote sensing image change captioning (RSICC) aims to describe surface changes
between multitemporal remote sensing images in language, including the changed object …
between multitemporal remote sensing images in language, including the changed object …
On the foundations of earth and climate foundation models
XX Zhu, Z **ong, Y Wang, AJ Stewart, K Heidler… - arxiv preprint arxiv …, 2024 - arxiv.org
Foundation models have enormous potential in advancing Earth and climate sciences,
however, current approaches may not be optimal as they focus on a few basic features of a …
however, current approaches may not be optimal as they focus on a few basic features of a …