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FishSegSSL: A Semi-Supervised Semantic Segmentation Framework for Fish-Eye Images

Author(s): Paul S; Patterson Z; Bouguila N;

The application of large field-of-view (FoV) cameras equipped with fish-eye lenses brings notable advantages to various real-world computer vision applications, including autonomous driving. While deep learning has proven successful in conventional computer vision applications using regular perspective images, its potential in fish-eye camera contexts rem ...

Article GUID: 38535151


Sharp U-Net: Depthwise convolutional network for biomedical image segmentation

Author(s): Zunair H; Ben Hamza A;

The U-Net architecture, built upon the fully convolutional network, has proven to be effective in biomedical image segmentation. However, U-Net applies skip connections to merge semantically different low- and high-level convolutional features, resulting in not only blurred feature maps, but also over- and under-segmented target regions. To address these ...

Article GUID: 34348214


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