Search Results for author:
Found 13 papers, 7 papers with code
Identifying every building's function in large-scale urban areas with multi-modality remote-sensing data
In this study, we proposed a semi-supervised framework to identify every building's function in large-scale urban areas with multi-modality remote-sensing data.
Generalized Few-Shot Meets Remote Sensing: Discovering Novel Classes in Land Cover Mapping via Hybrid Semantic Segmentation Framework
Land-cover mapping is one of the vital applications in Earth observation, aiming at classifying each pixel's land-cover type of remote-sensing images.
Learning without Exact Guidance: Updating Large-scale High-resolution Land Cover Maps from Low-resolution Historical Labels
However, it is still a non-trivial task hindered by complex ground details, various landforms, and the scarcity of accurate training labels over a wide-span geographic area.
Cross-level Attention with Overlapped Windows for Camouflaged Object Detection
In this paper, we propose an overlapped window cross-level attention (OWinCA) to achieve the low-level feature enhancement guided by the highest-level features.
Building Extraction from Remote Sensing Images via an Uncertainty-Aware Network
Building extraction aims to segment building pixels from remote sensing images and plays an essential role in many applications, such as city planning and urban dynamic monitoring.
Ranked #1 on
Semantic Segmentation
on INRIA Aerial Image Labeling
Degradation-Noise-Aware Deep Unfolding Transformer for Hyperspectral Image Denoising
However, model-based approaches rely on hand-crafted priors and hyperparameters, while learning-based methods are incapable of estimating the inherent degradation patterns and noise distributions in the imaging procedure, which could inform supervised learning.
MSFA-Frequency-Aware Transformer for Hyperspectral Images Demosaicing
The advantage of Maformer is that it can leverage the MSFA information and non-local dependencies present in the data.
National-scale 1-m resolution land-cover mapping for the entire China based on a low-cost solution and open-access data
With the rapid urbanization of China, there is an urgent need for creating a very-high-resolution (VHR) national-scale LC map for China.
Transition Is a Process: Pair-to-Video Change Detection Networks for Very High Resolution Remote Sensing Images
In view of these issues, we propose a more explicit and sophisticated modeling of time and accordingly establish a pair-to-video change detection (P2V-CD) framework.
Ranked #1 on
Change Detection
on CDD Dataset (season-varying)
Building change detection for remote sensing images
Change Detection
+3
Towards Complex Backgrounds: A Unified Difference-Aware Decoder for Binary Segmentation
In Stage A, the first branch decoder of the difference-aware decoder is used to obtain a guide map.
ESCNet: An End-to-End Superpixel-Enhanced Change Detection Network for Very-High-Resolution Remote Sensing Images
In this article, we propose an end-to-end superpixel-enhanced CD network (ESCNet) for VHR images, which combines differentiable superpixel segmentation and a deep convolutional neural network (DCNN).
Ranked #15 on
Change Detection
on CDD Dataset (season-varying)
Change Detection
Change detection for remote sensing images
+2
Non-local Meets Global: An Iterative Paradigm for Hyperspectral Image Restoration
Non-local low-rank tensor approximation has been developed as a state-of-the-art method for hyperspectral image (HSI) restoration, which includes the tasks of denoising, compressed HSI reconstruction and inpainting.
Shortest Paths in HSI Space for Color Texture Classification
Color texture representation is an important step in the task of texture classification.
