An Automatic broad colorization approach using Deep Learning
Dr. Subedha
, Sangavi R , Snega S , Swetha G , Lekasre.S
Automatic methods, black-and-white image, colorization, deep learning methods, image quality assessment, Grayscale images
The basic objective of colorization, which transforms grayscale images into aesthetically appealing colour images, is to persuade the user with reliable results. In this project, we apply deep learning methodology because user- guided methods requires more user interaction to produce a colorized image. Deep learning is used since it is a totally autonomous model and creates photos with accurate colors and contrast. Convolutional neural networks are used as a tool to automate the colouring process because we are aware of how laborious conventional methods are and because deep learning has many advantages (CNNs). A CNN is a particular kind of network architecture used by deep learning algorithms to process pixel input and perform tasks like image identification. Although there are many various types of neural networks used in deep learning, CNNs are the most commonly used network design for identifying and recognising objects. The neural network model automatically creates a function that converts a grayscale image's pixel properties to color values.
"An Automatic broad colorization approach using Deep Learning", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.429-435, February-2024, Available :https://tijer.org/TIJER/papers/TIJERB001067.pdf
Volume 11
Issue 2,
February-2024
Pages : 429-435
Paper Reg. ID: TIJER_151044
Published Paper Id: TIJERB001067
Downloads: 000274
Research Area: Science and Technology
Country: Tiruvallur, Tamil Nadu, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
