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 ...

Encoder Decoder Based Deep Learning Architecture For Video Scene Parsing Abstract: Due to its use in a variety of fields, including autonomous driving, ... To enhance the precision of the performance ...

Encoder-Decoder Architectures. Encoder-decoder architectures are a broad category of models used primarily for tasks that involve transforming input data into output data of a different form or ...

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 two-part machine that translates one form ...

In this project, I implemented a chatbot using the encoder-decoder algorithm as part of my exploration into the field of deep learning. The encoder-decoder architecture has gained widespread attention ...

Since the deep learning boom has started, numerous researchers have started building many architectures around neural networks. It is often speculated that the neural networks are inspired by neurons ...

Quantile-Based Encoder-Decoder Deep Learning Models for Multi-Step Ahead Hydrological Forecasting [Conference presentation]. American Geophysical Union (AGU) Fall Meeting 2022, Online. Recent ...

Encoder Decoder Based Deep Learning Architecture For Video Scene Parsing Abstract: Due to its use in a variety of fields, including autonomous driving, robot navigation, ... (VGG16 and VGG19) ...