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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | Literature Survey on Semantic Segmentation |
| Authors Name: | Dhanapriya B , Kavitha S , Baskaran K R |
| Download E-Certificate: | Download |
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IJRTI_182479
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| Published Paper Id: | IJRTI2206272 |
| Published In: | Volume 7 Issue 6, June-2022 |
| DOI: | |
| Abstract: | Annotating images is the most important task in creating AI applications. Datasets for computer vision models are generated through image annotation task in which training sets are used to train models, and test/validation sets are used to evaluate their performance. For functional datasets, labelling is necessary because it enables the training model to identify the important parts of the image (classes) so that it can identify those classes later on in new, previously undocumented images.Image Annotation can be done manually or with computer assistance. An entire image can be manually labelled or regions on an image can be drawn by humans.Manual annotation is a time consuming process and also it is prone to more errors.These limitations led to the growth of automatic image annotation.Automated image annotation involves assigning labels to digital images that describe the picture's content in the best way..Automatic image annotation is a faster process and also results in greater accuracy compared to manual annotation process. It is possible to annotate images in several ways, but the most advanced way is through segmentation. The task of segmenting an image entails grouping together parts that share the same class of objects.Segmentation process involves assigning pixel to specific category to which they belong to. Different methods of segmentation can be utilized, but semantic segmentation is the most intensive form of segmentation.The semantic segmentation technique is a deep pixel-by-pixel classification technique, and a segmentation model is a special library that supports multiple architectures for semantic segmentation.A review of different architectures used in the semantic segmentation process is presented in this paper in a broader perspective. |
| Keywords: | UNET, Semantic Segmentation, CNN |
| Cite Article: | "Literature Survey on Semantic Segmentation", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 6, page no.1827 - 1829, June-2022, Available :http://www.ijrti.org/papers/IJRTI2206272.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2206272
Registration ID:182479
Published In: Volume 7 Issue 6, June-2022
DOI (Digital Object Identifier):
Page No: 1827 - 1829 Country: Coimbatore, Tamil Nadu, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2206272 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2206272 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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