Visual Question Answering using Convolutional Neural Networks

The ability of a computer system to be able understand surroundings and elements think like human being process the information has always been major point focus in field Computer Science. One ways achieve this artificial intelligence is Visual Question Answering. Answering (VQA) trained which can answer questions associated given image Natural Language. VQA generalized used any image-based scenario with adequate training on relevant data. This achieved help Neural Networks, particularly Convolutional Network (CNN) Recurrent (RNN). In study, we have compared different approaches VQA, out are exploring CNN based model. With continued progress Vision answering system, becoming essential handle multiple scenarios their respective