Semantic segmentation is critical in medical image processing, with traditional specialist models facing adaptation challenges to new tasks or distribution shifts. While both generalist pre-trained ...

Abstract Seamlessly blending features from multiple images is extremely challenging because of complex relationships in lighting, geometry, and partial occlusion which cause coupling between different ...

Abstract: In this article a novel approach for separation of fish image regions implementing instance coefficients and separating masks is proposed. After considering the instance-specific ...

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A completed system for segmenting handwritten Armenian letters in images using binary masks. The project accurately identifies and isolates letter regions in the Mashtots dataset through binary image ...

To address the trade-off between segmentation performance and model lightweighting in computer-aided skin lesion segmentation, this paper proposes a lightweight network architecture, Multi-Conv ...

Abstract: We propose a novel pipeline for the generation of synthetic full spatial cine cardiac magnetic resonance (CMR) images via a latent Denoising Diffusion Implicit Models (DDIMs). These ...

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