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Found 5 papers, 3 papers with code
Spatial Coherence Loss for Salient and Camouflaged Object Detection and Beyond
We also demonstrate that combining SCLoss with other loss functions can further improve performance and result in the SOTA outcomes for different applications.
Directional Connectivity-based Segmentation of Medical Images
To this end, we propose a directional connectivity modeling scheme for segmentation that decouples, tracks, and utilizes the directional information across the network.
RetiFluidNet: A Self-Adaptive and Multi-Attention Deep Convolutional Network for Retinal OCT Fluid Segmentation
Experimental results on the datasets prove the effectiveness of the proposed model in retinal OCT fluid segmentation and reveal that the suggested method is more effective than existing state-of-the-art fluid segmentation algorithms in adapting to retinal OCT scans recorded by various image scanning instruments.
BiconNet: An Edge-preserved Connectivity-based Approach for Salient Object Detection
Salient object detection (SOD) is viewed as a pixel-wise saliency modeling task by traditional deep learning-based methods.
Multimodal Densenet
In this work, we propose Multimodal DenseNet, a novel architecture for fusing multimodal data.
