This repository contains a deep learning-based medical image segmentation system developed at the Budapest University of Technology and Economics. The system utilizes an encoder-decoder architecture, ...

The model leverages the Inception v3 pre-trained model for feature extraction from images and an LSTM-based decoder to generate captions. The architecture follows an encoder-decoder structure where ...

To this end, we introduce, a multi-scale encoder-decoder self-attention (MEDUSA ... An interesting future direction is to leverage the proposed MEDUSA architecture for the purpose of CT image analysis ...

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 ...

Are they text, speech, images, or something else? Depending on the modality, you might need a different encoder-decoder architecture that can handle the specific features and challenges of each ...

What Is An Encoder-Decoder Architecture? An encoder-decoder architecture is a powerful tool used in machine learning, specifically for tasks involving sequences like text or speech. It’s like a ...

The convolutional layers in the encoder and the deconvolution layers in the decoder are organized symmetrically. The decoder will reconstruct the input image using the features learned by the encoder.