International Journal of Advanced Innovative Technology in Engineering (IJAITE)

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Object Caption Generator Using Deep Learning

Prof. A. R. Ghongade, Sneha Zade, Yash Malankar, Sameer Kamble, Pranali Dhenge

Abstract :

In this project, we use CNN and LSTM to identify the caption of the object. As the deep learning techniques are growing, huge datasets and computer power are helpful to build models that can generate captions for an object. This is what we are going to implement in this Python based project where we will use deep learning techniques like CNN and RNN. Object caption generator is a process which involves natural language processing and computer vision concepts to recognize the context of an object and present it in English. In this survey, we carefully follow some of the core concepts of object captioning and its common approaches. We discuss Keras library, numpy and Pycharm for the making of this project.We also discuss about flickr_dataset and CNN used for object classification. The system is trained on a large dataset of objects and their corresponding captions, using techniques such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs). The CNNs are used to extract features from the objects, while the RNNs are used to generate the textual descriptions. The object caption generator is a promising application of machine learning in the field of computer vision. It has many potential uses, including assisting the visually impaired, creating better search results for object-based queries, and helping with content creation for social media and marketing purposes.

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