Encoder-Decoder Architecture CNN Encoder: The CNN serves as the feature extractor in our architecture. We use a pre-trained CNN model, specifically either VGG16 or ResNet-50, which are known for their ...

ABSTRACT: This paper presents an image captioning model that combines a Convolutional Neural Network (CNN) as an encoder to extract visual features from images, and a Long Short-Term Memory (LSTM) ...

1] Use free Base64 to Image converter software to decode Base64 images You can use dedicated software that allows you to encode and decode Base64 images. You can find some free ones on the web.

In this research work, EfficientNetV2B0 is utilized in the encoder part, for extracting objects from an image. Then Long Short-Term Memory (LSTM), a type of recurrent neural network as a decoder for ...

Since both encoder and decoder models are learned (meaning they can be re-trained), the same encoder or decoder architecture can be specialised for different tasks.

In the proposed method, mid-level document image representations are learnt by a stack of convolutional layers, which compose the encoder in this architecture. Then the binarization image is obtained ...

Because the decoder of layer 5 does not receive any information from the decoder, it only needs to connect the encoder of this layer and the middle layer. 3.6 Images enhancement. Image enhancement is ...