The Encoder-Decoder architecture is widely used in sequence-to-sequence tasks such as machine translation, text summarization, and speech recognition. However, traditional Encoder-Decoder models face ...

Two approaches were implemented, models, one without out attention using repeat vector, and the other using encoder decoder architecture and attention mechanism. nlp natural-language-processing ...

Finally, the decoder network learns the mapping from low-resolution feature maps to pixel-wise predictions for image tamper localization. With the predicted mask provided by the final layer (softmax) ...

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 ...

Due to its use in a variety of fields, including autonomous driving, robot navigation, remote sensing, medical research, agriculture etc.,In recent years, video scene parsing (VSP) has become ...

Such a capability is essential to making AI-based surrogate models practically useful. While simple feedforward networks are used for one-dimensional (1D) Poisson equation, an encoder-decoder ...