7 papers
Bridging Supervision Gaps: A Unified Framework for Remote Sensing Change Detection
Kaixuan Jiang, Chen Wu, Zhenghui Zhao +3
Change detection (CD) aims to identify surface changes from multi-temporal remote sensing imagery. In real-world scenarios, Pixel-level change labels are expensive to acquire, and…
MergeSAM: Unsupervised change detection of remote sensing images based on the Segment Anything Model
Meiqi Hu, Lingzhi Lu, Chengxi Han +1
Recently, large foundation models trained on vast datasets have demonstrated exceptional capabilities in feature extraction and general feature representation. The ongoing advancem…
MT-CYP-Net: Multi-Task Network for Pixel-Level Crop Yield Prediction Under Very Few Samples
Shenzhou Liu, Di Wang, Haonan Guo +2
Accurate and fine-grained crop yield prediction plays a crucial role in advancing global agriculture. However, the accuracy of pixel-level yield estimation based on satellite remot…
HSANET: A Hybrid Self-Cross Attention Network For Remote Sensing Change Detection
Chengxi Han, Xiaoyu Su, Zhiqiang Wei +2
The remote sensing image change detection task is an essential method for large-scale monitoring. We propose HSANet, a network that uses hierarchical convolution to extract multi-s…
Open-CD: A Comprehensive Toolbox for Change Detection
Kaiyu Li, Jiawei Jiang, Andrea Codegoni +13
We present Open-CD, a change detection toolbox that contains a rich set of change detection methods as well as related components and modules. The toolbox started from a series of…
HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model
Di Wang, Meiqi Hu, Yao Jin +19
Accurate hyperspectral image (HSI) interpretation is critical for providing valuable insights into various earth observation-related applications such as urban planning, precision…