TY - GEN
T1 - Natural language image descriptor
AU - Kishore, Anurag
AU - Singh, Sanjay
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/6/9
Y1 - 2016/6/9
N2 - Generating descriptions for visual data (images and video) automatically has been a complicated task in the field of Computer Vision and Artificial Intelligence. This paper discusses the working of and improvements on an algorithm called Neural Image Captioner (NIC) by Oriol Vinyals and his team, which uses a deep convolutional and recurrent architecture to generate natural language sentences to describe the visual data input. We look at the possibility of making this algorithm train faster without allowing it to lose accuracy via the usage of techniques like Stochastic Gradient Descent and also employ an algorithm to find the perfect depth of the convolutional part of the network for different datasets. A drop of 33% was observed in the number of iterations required to get the algorithm to its original proficiency as claimed by Oriol et al.
AB - Generating descriptions for visual data (images and video) automatically has been a complicated task in the field of Computer Vision and Artificial Intelligence. This paper discusses the working of and improvements on an algorithm called Neural Image Captioner (NIC) by Oriol Vinyals and his team, which uses a deep convolutional and recurrent architecture to generate natural language sentences to describe the visual data input. We look at the possibility of making this algorithm train faster without allowing it to lose accuracy via the usage of techniques like Stochastic Gradient Descent and also employ an algorithm to find the perfect depth of the convolutional part of the network for different datasets. A drop of 33% was observed in the number of iterations required to get the algorithm to its original proficiency as claimed by Oriol et al.
UR - https://www.scopus.com/pages/publications/84979009562
UR - https://www.scopus.com/inward/citedby.url?scp=84979009562&partnerID=8YFLogxK
U2 - 10.1109/RAICS.2015.7488398
DO - 10.1109/RAICS.2015.7488398
M3 - Conference contribution
AN - SCOPUS:84979009562
T3 - 2015 IEEE Recent Advances in Intelligent Computational Systems, RAICS 2015
SP - 110
EP - 115
BT - 2015 IEEE Recent Advances in Intelligent Computational Systems, RAICS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 IEEE Recent Advances in Intelligent Computational Systems, RAICS 2015
Y2 - 10 December 2015 through 12 December 2015
ER -