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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM24473

IMAGE SEGMENTATION USING DEEP LEARNING TECHNIQUES

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM24473

Volume:

7 |

7 |

Jul 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

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License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

GS

G.Mythri Sri

GNTR

G. Naga Thanishq Reddy

GN

G. Nikhitha

GNK

G. Nithin Kumar

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Abstract

Color image segmentation is an important task in computer vision, which involves partitioning an image into different regions based on their color similarity. In recent years, deep learning has emerged as a powerful tool for image segmentation. The use of convolutional neural networks (CNNs) has shown promising results in various applications, including color image segmentation. The process of color image segmentation using deep learning typically involves training a CNN on a large dataset of labeled images, where each pixel in the image is assigned, a label corresponding to its segment. During training, the network learns to extract features from the input image and use them to classify each pixel into its corresponding segment. The trained network can then be used to segment new images.

KEYWORDS

Image segmentation Convolutional Neural Networks (CNNs) Numerical digits Recognition accuracy robustness Computational efficiency Pre-processing techniques Communication accessibility Assistive technology.

Cite This Article

G.Mythri Sri, G. Naga Thanishq Reddy, G. Nikhitha, G. Nithin Kumar, "IMAGE SEGMENTATION USING DEEP LEARNING TECHNIQUES," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 7, Jul 2023. https://doi.org/10.55041/IJSREM24473

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Publication Date

10/6/2023

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Review Rounds: 2

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