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Pugan: Physical model-guided underwater image enhancement using gan with dual-discriminators
Due to the light absorption and scattering induced by the water medium, underwater images
usually suffer from some degradation problems, such as low contrast, color distortion, and …
usually suffer from some degradation problems, such as low contrast, color distortion, and …
CIR-Net: Cross-modality interaction and refinement for RGB-D salient object detection
Focusing on the issue of how to effectively capture and utilize cross-modality information in
RGB-D salient object detection (SOD) task, we present a convolutional neural network …
RGB-D salient object detection (SOD) task, we present a convolutional neural network …
MSNet: Multi-scale in Multi-scale Subtraction Network for Medical Image Segmentation
Accurate medical image segmentation is critical for early medical diagnosis. Most existing
methods are based on U-shape structure and use element-wise addition or concatenation to …
methods are based on U-shape structure and use element-wise addition or concatenation to …
Frequency perception network for camouflaged object detection
Camouflaged object detection (COD) aims to accurately detect objects hidden in the
surrounding environment. However, the existing COD methods mainly locate camouflaged …
surrounding environment. However, the existing COD methods mainly locate camouflaged …
Does thermal really always matter for RGB-T salient object detection?
In recent years, RGB-T salient object detection (SOD) has attracted continuous attention,
which makes it possible to identify salient objects in environments such as low light by …
which makes it possible to identify salient objects in environments such as low light by …
CD-Net: Cascaded 3D Dilated convolutional neural network for pneumonia lesion segmentation
COVID-19 is a global pandemic that has caused significant global, social, and economic
disruption. To effectively assist in screening and monitoring diagnosed cases, it is crucial to …
disruption. To effectively assist in screening and monitoring diagnosed cases, it is crucial to …
A weakly supervised learning framework for salient object detection via hybrid labels
Fully-supervised salient object detection (SOD) methods have made great progress, but
such methods often rely on a large number of pixel-level annotations, which are time …
such methods often rely on a large number of pixel-level annotations, which are time …
Decoupling and integration network for camouflaged object detection
Recently, camouflaged object detection (COD), which suffers from numerous challenges
such as low contrast between camouflaged objects and background and large variations of …
such as low contrast between camouflaged objects and background and large variations of …
Boundary guided semantic learning for real-time COVID-19 lung infection segmentation system
The coronavirus disease 2019 (COVID-19) continues to have a negative impact on
healthcare systems around the world, though the vaccines have been developed and …
healthcare systems around the world, though the vaccines have been developed and …
PSNet: Parallel symmetric network for video salient object detection
For the video salient object detection (VSOD) task, how to excavate the information from the
appearance modality and the motion modality has always been a topic of great concern. The …
appearance modality and the motion modality has always been a topic of great concern. The …