The UNet architecture follows the encoder-decoder paradigm. Encoder: The encoder part captures the contextual information from the input image. It consists of repeated applications of convolutional ...

In this project, I implemented a UNet model for semantic segmentation. The UNet architecture is particularly well-suited for biomedical image segmentation due to its symmetric structure, which ...

Illustrations of different types of encoders, the structures of encoders (A–C) are derived from UNet's encoder, decoder, and full structure, respectively. C1 represents a feature map of the same size ...

To overcome these two problems, we propose a Multi-Encoder Decoder UNet architecture, that can extract features at multiple spatial extents in an efficient way. We have evaluated our framework on two ...

Diffusion models, integral in text-to-video and reference-guided image generation, leverage the UNet architecture, comprising an encoder, bottleneck, and decoder. While past research focused on the ...

Abstract: The current state-of-the-art works in chest x-ray seg-mentation are based on the U-Net architecture, originally designed and developed for semantic segmentation. The U-Net base model uses a ...