Image synthesis using convolutional neural network

Ganesh  Bhat; Shrikant Dharwadkar; N. V.Subba Reddy; Shivaprasad  G

doi:10.1109/RTEICT.2017.8256685

Image synthesis using convolutional neural network

Ganesh Bhat, Shrikant Dharwadkar, N. V.Subba Reddy, Shivaprasad G

Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

The image processing task for conversion of image style is a tedious task. The previous approaches carried out in this area lacked in extracting higher level of abstractions from the input image, hence failed to generate image content from the acquired knowledge. Hence to achieve higher level knowledge from the object to be recognized, we make use of convolutional neural networks which aid in achieving higher quality images. The proposed work uses a Neural Algorithm that produces an image with a new style using the knowledge acquired from input image. Our work provides a new approach for deep representations of images using Neural Networks, hence demonstrating the generation of high level image synthesis and manipulation.

Original language	English
Title of host publication	RTEICT 2017 - 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	689-691
Number of pages	3
Volume	2018-January
ISBN (Electronic)	9781509037049
DOIs	https://doi.org/10.1109/RTEICT.2017.8256685
Publication status	Published - 12-01-2017
Event	2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2017 - Bangalore, India Duration: 19-05-2017 → 20-05-2017

Conference

Conference	2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2017
Country/Territory	India
City	Bangalore
Period	19-05-17 → 20-05-17

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Computer Science Applications
Media Technology
Control and Optimization
Instrumentation
Transportation
Communication

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10.1109/RTEICT.2017.8256685

Cite this

Bhat, G., Dharwadkar, S., Reddy, N. V. S., & G, S. (2017). Image synthesis using convolutional neural network. In RTEICT 2017 - 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, Proceedings (Vol. 2018-January, pp. 689-691). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RTEICT.2017.8256685

@inproceedings{e9db7b378419400dbeb3c6f7dd8218f8,

title = "Image synthesis using convolutional neural network",

abstract = "The image processing task for conversion of image style is a tedious task. The previous approaches carried out in this area lacked in extracting higher level of abstractions from the input image, hence failed to generate image content from the acquired knowledge. Hence to achieve higher level knowledge from the object to be recognized, we make use of convolutional neural networks which aid in achieving higher quality images. The proposed work uses a Neural Algorithm that produces an image with a new style using the knowledge acquired from input image. Our work provides a new approach for deep representations of images using Neural Networks, hence demonstrating the generation of high level image synthesis and manipulation.",

author = "Ganesh Bhat and Shrikant Dharwadkar and Reddy, {N. V.Subba} and Shivaprasad G",

year = "2017",

month = jan,

day = "12",

doi = "10.1109/RTEICT.2017.8256685",

language = "English",

volume = "2018-January",

pages = "689--691",

booktitle = "RTEICT 2017 - 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2017 ; Conference date: 19-05-2017 Through 20-05-2017",

}

Bhat, G, Dharwadkar, S, Reddy, NVS & G, S 2017, Image synthesis using convolutional neural network. in RTEICT 2017 - 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, Proceedings. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 689-691, 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2017, Bangalore, India, 19-05-17. https://doi.org/10.1109/RTEICT.2017.8256685

Image synthesis using convolutional neural network. / Bhat, Ganesh; Dharwadkar, Shrikant; Reddy, N. V.Subba et al.
RTEICT 2017 - 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, Proceedings. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 689-691.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Image synthesis using convolutional neural network

AU - Bhat, Ganesh

AU - Dharwadkar, Shrikant

AU - Reddy, N. V.Subba

AU - G, Shivaprasad

PY - 2017/1/12

Y1 - 2017/1/12

N2 - The image processing task for conversion of image style is a tedious task. The previous approaches carried out in this area lacked in extracting higher level of abstractions from the input image, hence failed to generate image content from the acquired knowledge. Hence to achieve higher level knowledge from the object to be recognized, we make use of convolutional neural networks which aid in achieving higher quality images. The proposed work uses a Neural Algorithm that produces an image with a new style using the knowledge acquired from input image. Our work provides a new approach for deep representations of images using Neural Networks, hence demonstrating the generation of high level image synthesis and manipulation.

AB - The image processing task for conversion of image style is a tedious task. The previous approaches carried out in this area lacked in extracting higher level of abstractions from the input image, hence failed to generate image content from the acquired knowledge. Hence to achieve higher level knowledge from the object to be recognized, we make use of convolutional neural networks which aid in achieving higher quality images. The proposed work uses a Neural Algorithm that produces an image with a new style using the knowledge acquired from input image. Our work provides a new approach for deep representations of images using Neural Networks, hence demonstrating the generation of high level image synthesis and manipulation.

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DO - 10.1109/RTEICT.2017.8256685

M3 - Conference contribution

VL - 2018-January

SP - 689

EP - 691

BT - RTEICT 2017 - 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 19 May 2017 through 20 May 2017

ER -

Image synthesis using convolutional neural network

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