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HDFNet: Hierarchical Dynamic Fusion Network for Change Detection in Optical Aerial Images

Yi Zhang, Lei Fu, Ying Li, Yanning Zhang
2021 Remote Sensing  
To deal with these problems, we design a hierarchical dynamic fusion network (HDFNet) to implement the optical aerial image-change detection task.  ...  Accurate change detection in optical aerial images by using deep learning techniques has been attracting lots of research efforts in recent years.  ...  Conclusions In this paper, an HDFNet is proposed to conduct the optical aerial images change detection.  ... 
doi:10.3390/rs13081440 fatcat:ox2oot42pjcybpgehvbwst56ei

MAFF-Net: Multi-Attention Guided Feature Fusion Network for Change Detection in Remote Sensing Images

Jinming Ma, Gang Shi, Yanxiang Li, Ziyu Zhao
2022 Sensors  
One of the most important tasks in remote sensing image analysis is remote sensing image Change Detection (CD), and CD is the key to helping people obtain more accurate information about changes on the  ...  A Multi-Attention Guided Feature Fusion Network (MAFF-Net) for CD tasks has been designed. The network enhances feature extraction and feature fusion by building different blocks.  ...  In addition, in 2021, HDFNet [47] uses the idea of a hierarchical fusion and dynamic convolution model to obtain a fine feature map.  ... 
doi:10.3390/s22030888 pmid:35161634 pmcid:PMC8838741 fatcat:jdcd3sjyjrdhvhso3lb3anwvei

An Efficient Lightweight Neural Network for Remote Sensing Image Change Detection

Kaiqiang Song, Fengzhi Cui, Jie Jiang
2021 Remote Sensing  
Remote sensing (RS) image change detection (CD) is a critical technique of detecting land surface changes in earth observation.  ...  Deep learning (DL)-based approaches have gained popularity and have made remarkable progress in change detection.  ...  [34] proposed a hierarchical network, called HDFNet, which introduces dynamic convolution modules into decoding stages for emphasizing feature fusion.  ... 
doi:10.3390/rs13245152 fatcat:jilyf52avjg27kzw3rttytumom