Jun 22, 2022 · In this work, a 2D U-net network with embedded Inception-ResNet-v2 blocks was used for automated segmentation of head and neck CT scans. In general, U-net is a …

In this study, we proposed a residually connected, Inception-based, u-shaped encoder–decoder architecture with skip connections named as Residual-Inception U-Net (RIU-Net). The model …

Jan 13, 2023 · To extract building, in this paper two segmentation architectures, the UNet and the Inception ResNet UNet are implemented and then tested on the Inria aerial image datasets. …

Jun 22, 2022 · The segmentation model was based on the U-Net architecture with embedded Inception-ResNet-v2 blocks and was trained over 100 epochs with a batch size of 32 and an …

Inception ResNet UNet architectures. Inception ResNet UNet is an improvement on UNet to solve the convergence problem for deeper encoder-decoder layers. The bing deeper and wider of …

Oct 15, 2024 · This paper introduces a novel deep learning-based approach using an enhanced encoder-decoder architecture, where the Inception-ResNet-v2 model serves as the encoder. …

In the paper, a new deep learning architecture has been developed by combining inception blocks with the convolutional layers of the original U-Net architecture to achieve remarkably high …

Feb 22, 2025 · We developed a hybrid model utilizing the Inception-ResNet-v2 and Inception-dResNet-v2 architectures, specifically designed to classify the severity of COVID-19 into ten …

This is the first instance of utilizing Inception-ResNet-v2 as an encoder for monocular depth estimation, demonstrating improved performance over previous models. It incorporates multi …

Apr 10, 2019 · Both the Inception and Residual networks are SOTA architectures, which have shown very good performance with relatively low computational cost. Inception-ResNet …