The problem is sometimes called “ automatic image annotation” or “ image tagging.” This post is divided into 3 parts they are:ĭescribing an image is the problem of generating a human-readable textual description of an image, such as a photograph of an object or scene. Kick-start your project with my new book Deep Learning for Natural Language Processing, including step-by-step tutorials and the Python source code files for all examples. How the elements of the model can be arranged into an Encoder-Decoder, possibly with the use of an attention mechanism.About the elements that comprise a neural feature captioning model, namely the feature extractor and language model.About the challenge of generating textual descriptions for images and the need to combine breakthroughs from computer vision and natural language processing.In this post, you will discover how deep neural network models can be used to automatically generate descriptions for images, such as photographs.Īfter completing this post, you will know: Recently, deep learning methods have displaced classical methods and are achieving state-of-the-art results for the problem of automatically generating descriptions, called “captions,” for images. It is an easy problem for a human, but very challenging for a machine as it involves both understanding the content of an image and how to translate this understanding into natural language. Captioning an image involves generating a human readable textual description given an image, such as a photograph.
0 kommentar(er)
