UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 9 Issue 9
September-2022
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2209224


Registration ID:
500405

Page Number

c49-c54

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Title

Vision2Code: Transformation of Sketches to UI in Real-time Using Deep Neural Network

Abstract

In a Development Work Most of The Time we are spending our most of the precious time in developing UI prototypes and this can be tedious work, and it leaves very smaller window for building the actual logic and functionality for the product which alternatively affects the productivity. User Interface (UI) prototyping is a necessary step in the early stages of application development. Transforming sketches of a Graphical User Interface (UI) into a coded UI application is an uninspired but time-consuming task performed by a UI designer .Just imagine that the time that we are giving for developing The UI prototype, if we give the similar amount of time to make the system more robust and more functional then , how much efficient our product would be ? So to find the alternative of the above problem I am proposing the solution where we do not require to think about the HTML code for developing the UI, it will be completely automatic using the current advancement into the technology called Deep Neural network .Here You just need to draw a design ( wireframe ) on a white board or white paper and then using the Computer vision it will automatically generate the HTML output code for it . This could Help the developers to work efficiently and also it can save a lot of time of the employee and the company and saving the time of the company alternatively saves the money. The output of the project would be the code which can further modified according to the user requirement. The two main models which will play the main role here are convolution neural network and gated recurrent network. Here the model will be trained on the data which I will generate by me. Where I need to take the picture of the hand draw designs. And a last for the deployment point of you the webapp will be created which will give the user more user friendly environment where they just need to take the picture or they just need to upload it and the output will be printed of screen.

Key Words

Computer, CNN, deep neural network , GUI

Cite This Article

"Vision2Code: Transformation of Sketches to UI in Real-time Using Deep Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.c49-c54, September-2022, Available :http://www.jetir.org/papers/JETIR2209224.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Vision2Code: Transformation of Sketches to UI in Real-time Using Deep Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. ppc49-c54, September-2022, Available at : http://www.jetir.org/papers/JETIR2209224.pdf

Publication Details

Published Paper ID: JETIR2209224
Registration ID: 500405
Published In: Volume 9 | Issue 9 | Year September-2022
DOI (Digital Object Identifier):
Page No: c49-c54
Country: Aurangabad, maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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