U-Net architecture is a deep learning image segmentation architecture introduced by Olaf Ronneberger, Philipp Fischer, and Thomas Brox in 2015. Its U shape design consists of two parts. The left side ...

In this study, a deep learning-based model with an encoder–decoder structure was proposed for MRI image segmentation and application to glioma. The model obtained in the RegNet design space was ...

Against this backdrop, the broad success of deep learning (DL ... spectrum of pioneering efforts in semantic and instance segmentation, including convolutional pixel-labeling networks, encoder-decoder ...

Abstract: Dental image segmentation is an important task in ... Additionally, a novel deep learning methodology based on a dual stream encoder and decoder architecture is proposed for automatically ...

Image recognition has become a cornerstone of modern technology, transforming industries like healthcare, retail, automotive, and security. Deep learning techniques ... for biomedical image ...

Due to large variability in optical plant appearance and experimental setups, advanced machine and deep learning techniques are required for automated detection and segmentation ... details of the ...

SegNet is used here to solve a binary pixel-wise image segmentation task, where positive samples ... producing pixel-wise categorical segmentations using the very common encoder-decoder architecture.