We propose a new approach to address these issues by using multiple neighbourhoods around the pixel of interest and aggregating different hypotheses about the ...
Convolutional Neural Networks (CNNs) have been widely used in the semantic segmentation of medical im- ages. Current CNN-based approaches don't fully ...
This work proposes a new approach to address semantic segmentation of medical images by using multiple neighbourhoods around the pixel of interest and ...
We propose a new approach to address these issues by using multiple neighbourhoods around the pixel of interest and aggregating different hypotheses about the ...
Abstract—Convolutional Neural Networks (CNNs) have been widely used in the semantic segmentation of medical images. Current CNN-based approaches don't fully ...
In general, contexts that are modeled in image coordinates are vulnerable to the coordinate changes in higher spaces such as the varying pose of the mounted ...
This survey provides a comprehensive insight into DL-based medical image segmentation by covering its application domains, model exploration, analysis of state ...
Oct 20, 2023 · In this paper, we propose a new model that combines the strengths of both CNNs and Transformer, with network architectural improvements.
May 10, 2023 · In this paper, a convolutional network, named Adaptive Feature Fusion UNet (AFF-UNet), is proposed to optimize the semantic segmentation performance.
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Feb 26, 2024 · In this article, we will explore advanced techniques in semantic segmentation, focusing on the application of deep learning and neural networks.