Images have been divided into two groups, real images and mask images, at 256 pixels on the x-axis of each image. The U-Net architecture* has been implemented and trained with train images. (* U-Net ...

Encoder-Decoder with Convolution Layers convolutional layers provide various features to perform different tasks of image processing and using convolutional layers and pooling layers downsample the ...

Specifically, the DECTNet embraces four components, which are a convolution-based encoder, a Transformer-based encoder, a feature fusion decoder, and a deep supervision module. The convolutional ...

Convolutional Neural Network (CNN) is widely used in Hyperspectral Images (HSIs) classification. However, the fine-grained spatial (FGS) details are discarded during a sequence of convolution and ...

Constrained image splicing detection and localization (CISDL) is a newly formulated image forensics task and plays an important role in verifying the generating process of a forged image. CISDL ...

Huang, X. (2018) DeepLabv3+: Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. has been cited by the following article: TITLE: Recognition of Pointer Meter Readings ...

1370 Aim: Quantitative positron emission tomography (PET) image reconstruction is challenging due to the attenuation correction needed during the reconstruction process. In this study, we propose and ...

The encoder of SegNet is identical to the VGGNet architecture. Each stage of the encoder consist of a number of fixed repetition blocks of a convolution layer, a batch normalization layer, ReLu ...