WebIn this study, we present UTNet, a simple yet powerful hybrid Transformer architecture that integrates self-attention into a convolutional neural network for enhancing medical image segmentation. UTNet applies self-attention modules in both encoder and decoder for capturing long-range dependency at dif- ferent scales with minimal overhead. WebUTA Capital Development Integrated Project Control System Friday, April 14, 2024
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