[HTML][HTML] Skyeyegpt: Unifying remote sensing vision-language tasks via instruction tuning with large language model
Large language models (LLMs) have recently been extended to the vision-language realm,
obtaining impressive general multi-modal capabilities. However, the exploration of multi …
obtaining impressive general multi-modal capabilities. However, the exploration of multi …
When Geoscience Meets Foundation Models: Toward a general geoscience artificial intelligence system
Artificial intelligence (AI) has significantly advanced Earth sciences, yet its full potential in to
comprehensively modeling Earth's complex dynamics remains unrealized. Geoscience …
comprehensively modeling Earth's complex dynamics remains unrealized. Geoscience …
Multi-modal LLMs in agriculture: A comprehensive review
Given the rapid emergence and applications of Large Language Models (LLMs) across
various scientific fields, insights regarding their applicability in agriculture are still only …
various scientific fields, insights regarding their applicability in agriculture are still only …
Foundation Model-based Spectral-Spatial Transformer for Hyperspectral Image Classification
L Huang, Y Chen, X He - IEEE Transactions on Geoscience …, 2024 - ieeexplore.ieee.org
Recently, deep learning models have dominated hyperspectral image (HSI) classification.
Nowadays, deep learning is undergoing a paradigm shift with the rise of transformer-based …
Nowadays, deep learning is undergoing a paradigm shift with the rise of transformer-based …
Rs-moe: Mixture of experts for remote sensing image captioning and visual question answering
H Lin, D Hong, S Ge, C Luo, K Jiang, H **… - arxiv preprint arxiv …, 2024 - arxiv.org
Remote Sensing Image Captioning (RSIC) presents unique challenges and plays a critical
role in applications. Traditional RSIC methods often struggle to produce rich and diverse …
role in applications. Traditional RSIC methods often struggle to produce rich and diverse …
Leveraging visual language model and generative diffusion model for zero-shot sar target recognition
J Wang, H Sun, T Tang, Y Sun, Q He, L Lin… - Remote …, 2024 - search.proquest.com
Simulated data play an important role in SAR target recognition, particularly under zero-shot
learning (ZSL) conditions caused by the lack of training samples. The traditional SAR …
learning (ZSL) conditions caused by the lack of training samples. The traditional SAR …
Urbancross: Enhancing satellite image-text retrieval with cross-domain adaptation
Urbanization challenges underscore the necessity for effective satellite image-text retrieval
methods to swiftly access specific information enriched with geographic semantics for urban …
methods to swiftly access specific information enriched with geographic semantics for urban …
Chatearthnet: A global-scale, high-quality image-text dataset for remote sensing
An in-depth comprehension of global land cover is essential in Earth observation, forming
the foundation for a multitude of applications. Although remote sensing technology has …
the foundation for a multitude of applications. Although remote sensing technology has …
From Pixels to Prose: Advancing Multi-Modal Language Models for Remote Sensing
Remote sensing has evolved from simple image acquisition to complex systems capable of
integrating and processing visual and textual data. This review examines the development …
integrating and processing visual and textual data. This review examines the development …
HCNet: Hierarchical Feature Aggregation and Cross-Modal Feature Alignment for Remote Sensing Image Captioning
Remote sensing image captioning (RSIC) aims to describe the crucial objects from remote
sensing images in the form of natural language. The inefficient utilization of object texture …
sensing images in the form of natural language. The inefficient utilization of object texture …