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Found 13 papers, 10 papers with code
Frequency Decomposition-Driven Unsupervised Domain Adaptation for Remote Sensing Image Semantic Segmentation
Cross-domain semantic segmentation of remote sensing (RS) imagery based on unsupervised domain adaptation (UDA) techniques has significantly advanced deep-learning applications in the geosciences.
RS3Mamba: Visual State Space Model for Remote Sensing Images Semantic Segmentation
Experimental results on two widely used datasets, ISPRS Vaihingen and LoveDA Urban, demonstrate the effectiveness and potential of the proposed RS3Mamba.
Adaptive Semantic-Enhanced Denoising Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution
However, the high-frequency details generated by DDPM often suffer from misalignment with HR images due to the model's tendency to overlook long-range semantic contexts.
DF4LCZ: A SAM-Empowered Data Fusion Framework for Scene-Level Local Climate Zone Classification
The proposed method introduces a novel Dual-stream Fusion framework for LCZ classification (DF4LCZ), integrating instance-based location features from Google imagery with the scene-level spatial-spectral features extracted from Sentinel-2 imagery.
LLM-Assisted Light: Leveraging Large Language Model Capabilities for Human-Mimetic Traffic Signal Control in Complex Urban Environments
Specifically, a hybrid framework that augments LLMs with a suite of perception and decision-making tools is proposed, facilitating the interrogation of both the static and dynamic traffic information.
Diffusion Enhancement for Cloud Removal in Ultra-Resolution Remote Sensing Imagery
The presence of cloud layers severely compromises the quality and effectiveness of optical remote sensing (RS) images.
UniTSA: A Universal Reinforcement Learning Framework for V2X Traffic Signal Control
Traffic congestion is a persistent problem in urban areas, which calls for the development of effective traffic signal control (TSC) systems.
SAM-Assisted Remote Sensing Imagery Semantic Segmentation with Object and Boundary Constraints
Furthermore, the boundary loss capitalizes on the distinctive features of SGB by directing the model's attention to the boundary information of the object.
GCD-DDPM: A Generative Change Detection Model Based on Difference-Feature Guided DDPM
Furthermore, the Difference Conditional Encoder (DCE), is designed to guide the generation of CD maps by exploiting multi-level difference features.
GCRDN: Global Context-Driven Residual Dense Network for Remote Sensing Image Superresolution
To cope with this problem, this work proposes a novel global context-driven residual dense network (GCRDN) for satellite image SR based on the encoder and decoder architecture.
ADLight: A Universal Approach of Traffic Signal Control with Augmented Data Using Reinforcement Learning
In this paper, we propose a novel reinforcement learning approach with augmented data (ADLight) to train a universal model for intersections with different structures.
Rényi State Entropy for Exploration Acceleration in Reinforcement Learning
One of the most critical challenges in deep reinforcement learning is to maintain the long-term exploration capability of the agent.
Fairness-Oriented User Scheduling for Bursty Downlink Transmission Using Multi-Agent Reinforcement Learning
In this work, we develop practical user scheduling algorithms for downlink bursty traffic with emphasis on user fairness.
