We use the encoder-decoder model which in this case it would be Encoder : Convolutional Features For an image captioning system, we should use a trained architecture, such as ResNet or Inception, to ...

Generate caption on images using CNN Encoder- LSTM Decoder structure. This project is the second project of Udacity's Computer Vision Nanodegree and combines computer vision and machine translation ...

This article has also introduced a novel convolutional-encoder-decoder deep-neural-network (l,r-PanoED-network) with a unique split-encoding-network methodology, to stitch non-coherent input left, ...

CNNs excel in handling grid-like data such as images, RNNs are unparalleled in their ability to process sequential data, GANs offer remarkable capabilities in generating new data samples, Transformers ...

U-Net is characterized by its encoder-decoder architecture and pioneering skip connections, ... U-net, medical image segmentation, pulmonarty embolism, CNN -convolutional neural network. Citation: ...

In the context of US image segmentation, a dual-branch encoder combining Swin Transformer and CNN demonstrates significant enhancements. This is chiefly attributed to the self-attention mechanism of ...