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Found 5 papers, 3 papers with code
SFFNet: A Wavelet-Based Spatial and Frequency Domain Fusion Network for Remote Sensing Segmentation
In order to fully utilize spatial information for segmentation and address the challenge of handling areas with significant grayscale variations in remote sensing segmentation, we propose the SFFNet (Spatial and Frequency Domain Fusion Network) framework.
MFDS-Net: Multi-Scale Feature Depth-Supervised Network for Remote Sensing Change Detection with Global Semantic and Detail Information
We propose MFDS-Net: Multi-Scale Feature Depth-Supervised Network for Remote Sensing Change Detection with Global Semantic and Detail Information (MFDS-Net) with the aim of achieving a more refined description of changing buildings as well as geographic information, enhancing the localisation of changing targets and the acquisition of weak features.
DmADs-Net: Dense multiscale attention and depth-supervised network for medical image segmentation
In addition, in the feature fusion phase, a Feature Refinement and Fusion Block is created to enhance the fusion of different semantic information. We validated the performance of the network using five datasets of varying sizes and types.
Underwater Variable Zoom: Depth-Guided Perception Network for Underwater Image Enhancement
In this work, we investigate injecting the depth prior into the deep UIE model for more precise scene enhancement capability.
Image Shadow Removal Using End-to-End Deep Convolutional Neural Networks
Image degradation caused by shadows is likely to cause technological issues in image segmentation and target recognition.
