5 papers
SkyVLaM: Multimodal Large Language Model for UAV Video Understanding in Remote Sensing
Kaiwen Jing, Ruixu Jia, Bingyao Li +3
Recent advances in Multimodal Large Language Models (MLLMs) have significantly improved remote sensing (RS) multimodal understanding. Language-conditioned segmentation is crucial f…
MFogHub: Bridging Multi-Regional and Multi-Satellite Data for Global Marine Fog Detection and Forecasting
Mengqiu Xu, Kaixin Chen, Heng Guo +5
Deep learning approaches for marine fog detection and forecasting have outperformed traditional methods, demonstrating significant scientific and practical importance. However, the…
Enhancing Multi-task Learning Capability of Medical Generalist Foundation Model via Image-centric Multi-annotation Data
Xun Zhu, Fanbin Mo, Zheng Zhang +6
The emergence of medical generalist foundation models has revolutionized conventional task-specific model development paradigms, aiming to better handle multiple tasks through join…
M4Fog: A Global Multi-Regional, Multi-Modal, and Multi-Stage Dataset for Marine Fog Detection and Forecasting to Bridge Ocean and Atmosphere
Mengqiu Xu, Ming Wu, Kaixin Chen +11
Marine fog poses a significant hazard to global shipping, necessitating effective detection and forecasting to reduce economic losses. In recent years, several machine learning (ML…
Multi-Scale Representations by Varying Window Attention for Semantic Segmentation
Haotian Yan, Ming Wu, Chuang Zhang
Multi-scale learning is central to semantic segmentation. We visualize the effective receptive field (ERF) of canonical multi-scale representations and point out two risks in learn…