What is image captioning using deep learning?

Image Captioning is the process of generating a textual description for given images. It has been a very important and fundamental task in the Deep Learning domain. NVIDIA is using image captioning technologies to create an application to help people who have low or no eyesight.

What type of RNN is used for image captioning?

Long Short-Term Memory (LSTM) networks are a type of Recurrent Neural Network (RNN) capable of learning order dependence in sequence prediction problems. This is most commonly used in complex problems like Machine Translation, Speech Recognition, and many more.

Is image captioning supervised or unsupervised?

Unsupervised image captioning is similar in spirit to un- supervised machine translation, if we regard the image as the source language.

What is the need of image captioning?

Image captioning requires to recognize the important objects, their attributes and their relationships in an image. It also needs to generate syntactically and semantically correct sentences. Most images do not have a description, but the human can largely understand them without their detailed captions.

What is image caption generation?

Image caption Generator is a popular research area of Artificial Intelligence that deals with image understanding and a language description for that image. Generating well-formed sentences requires both syntactic and semantic understanding of the language.

What is image caption?

Image Captioning is the process of generating textual description of an image. It uses both Natural Language Processing and Computer Vision to generate the captions.

What is Flickr dataset?

Flickr Image captioning dataset The Flickr30k dataset has become a standard benchmark for sentence-based image description. They enable us to define a new benchmark for localization of textual entity mentions in an image.

What is CNN LSTM?

The CNN Long Short-Term Memory Network or CNN LSTM for short is an LSTM architecture specifically designed for sequence prediction problems with spatial inputs, like images or videos. About the development of the CNN LSTM model architecture for sequence prediction.

How many types of ANN are there?

This article focuses on three important types of neural networks that form the basis for most pre-trained models in deep learning: Artificial Neural Networks (ANN) Convolution Neural Networks (CNN) Recurrent Neural Networks (RNN)

What is CNN in image captioning?

Convolutional Neural Networks were designed to map image data to an output variable. They have proven so effective that they are the go-to method for any type of prediction problem involving image data as an input.

What is a caption example?

An example of a caption is the title of a magazine article. An example of a caption is a descriptive title under a photograph. An example of a caption are the words at the bottom of a television or movie screen to translate the dialogue into another language or to provide the dialogue to the hard of hearing.

In the project Image Captioning using deep learning, is the process of generation of textual description of an image and converting into speech using TTS. We introduce a synthesized audio output generator which localize and describe objects, attributes, and relationship in an image, in a natural language form.

How does our model to caption images work?

Our model to caption images are built on multimodal recurrent and convolutional neural networks. A Convolutional Neural Network is used to extract the features from an image which is then along with the captions is fed into an Recurrent Neural Network. The architecture of the image captioning model is shown in figure 1.

How many particular captions are generated from 30000 images?

In which it has 30,000 images with image id and a particular id has 5 captions generated. Here is the link to the dataset so that you can also download that dataset. Here are the particular captions for these images which is present in the dataset. 1 .Image Features Detection : For image Detecting, we are using a pre-trained model which is VGG16.

What is deep learning and neural network?

Deep Learning and Neural Network lies in the heart of products such as self-driving cars, image recognition software, recommender systems etc. Evidently, being a powerful algorithm, it is highly adaptive to various data types as well.