 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
|
Issue: December 2025
Volume 10 | Issue 12
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19451
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 144
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Deep Learning Model Using U-Net Architecture with Adam Algorithm for Image Segmentation |
| Authors Name: | Rakesh Prasanna R , Dr G Geetha |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_188622
|
| Published Paper Id: | IJRTI2312032 |
| Published In: | Volume 8 Issue 12, December-2023 |
| DOI: | |
| Abstract: | Image segmentation is the process of breaking a picture up into collections of pixel regions that are each represented by a mask or labelled image. Medical image segmentation involves the extraction of regions of interest (ROIs) from 3D image data, such as from Magnetic Resonance Imaging (MRI) or Computed Tomography (CT) scans. The main goal of segmenting this data is to identify areas of the anatomy required for a particular study. U-net is an image segmentation framework developed by CNN. The primary disadvantage of U-net is the slow learning rate at the deeper model's intermediate layers. Adam is a different optimization algorithm that can be used to teach deep learning models instead of stochastic gradient descent. Adam creates an optimization algorithm that can manage sparse gradients on noisy problems by combining the best elements of the Momentum and RMSProp algorithms. The learning rate will be increased by incorporating the Adam algorithm into the U-net design. The metrics used to find the performance of the Deep learning model built from the U-Net architecture is Dice Coefficient, loss value and as well as time required for each Epoch. |
| Keywords: | Image segmentation, stochastic gradient, learning rate, U-net, CNN, Adam algorithm |
| Cite Article: | "Deep Learning Model Using U-Net Architecture with Adam Algorithm for Image Segmentation ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 12, page no.235 - 242, December-2023, Available :http://www.ijrti.org/papers/IJRTI2312032.pdf |
| Downloads: | 000205228 |
| ISSN: |
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 |
| Publication Details: |
Published Paper ID: IJRTI2312032
Registration ID:188622
Published In: Volume 8 Issue 12, December-2023
DOI (Digital Object Identifier):
Page No: 235 - 242 Country: New Delhi, New Delhi, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2312032 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2312032 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2025 - All Rights Reserved - IJRTI | |||