An Encoder-Decoder model is a fundamental architecture in the field of deep learning and natural language processing (NLP). It's widely used for a variety of tasks, including machine translation, text ...

This project implements an Image Captioning model using a CNN-RNN architecture in PyTorch. The model leverages the Inception v3 pre-trained model for feature extraction from images and an LSTM-based ...

In unsupervised medical image registration, encoder-decoder architectures are widely used to predict dense, full-resolution displacement fields from paired images. Despite their popularity, we ...

TensorRT-LLM has long been a critical tool for optimizing inference in models such as decoder-only architectures like Llama 3.1, mixture-of-experts models like Mixtral, and selective state-space ...

Google is offering free AI courses that can help professionals and students to upskill themselves. From introduction into ...

Create Image Captioning Models You will learn about the many components of an image captioning model, including the encoder and decoder, how to train and evaluate. Transformer Models and BERT Model ...

Unsupervised anomaly detection (UAD) aims to recognize anomalous images based on the training set that contains only normal images. In medical image analysis, UAD benefits from leveraging the easily ...