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Reseach Article

An Effective Analysis of Image Processing with Deep Learning Algorithms

by G. Thippanna, and M. Devi Priya, T. Adithay Sai Srinivas
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 185 - Number 27
Year of Publication: 2023
Authors: G. Thippanna, and M. Devi Priya, T. Adithay Sai Srinivas
10.5120/ijca2023923014

G. Thippanna, and M. Devi Priya, T. Adithay Sai Srinivas . An Effective Analysis of Image Processing with Deep Learning Algorithms. International Journal of Computer Applications. 185, 27 ( Aug 2023), 1-5. DOI=10.5120/ijca2023923014

@article{ 10.5120/ijca2023923014,
author = { G. Thippanna, and M. Devi Priya, T. Adithay Sai Srinivas },
title = { An Effective Analysis of Image Processing with Deep Learning Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2023 },
volume = { 185 },
number = { 27 },
month = { Aug },
year = { 2023 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume185/number27/32857-2023923014/ },
doi = { 10.5120/ijca2023923014 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:27:09.364344+05:30
%A G. Thippanna
%A and M. Devi Priya
%A T. Adithay Sai Srinivas
%T An Effective Analysis of Image Processing with Deep Learning Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 185
%N 27
%P 1-5
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image processing finds applications in various fields, including medicine, remote sensing, surveillance, entertainment, and scientific research by using various algorithms and techniques. It involves transforming, enhancing, and extracting information from images to improve their quality, interpret their content, or make them suitable for specific applications.Deep learning algorithms are designed to automatically learn hierarchical representations of data through multiple layers of interconnected artificial neurons, known as artificial neural networks. These networks are organized into input, hidden, and output layers, with each layer consisting of numerous interconnected nodes or units called neurons. Each neuron applies a mathematical operation to the inputs it receives and passes the result to the next layer.When deep learning algorithms are applied to image processing, they can perform a wide range of tasks such as image classification, object detection, image segmentation, image generation, and image enhancement.

References
  1. Introduction to Convolutional Neural Networks by Jianxin Wu and Lamda Group Nanjing University, China, May 2017.
  2. Deep Learning (Adaptive Computation and Machine Learning series) by Aaron Courville (Author), Ian Goodfellow (Author), Yoshua Bengio (Author), in Nov 2018.
  3. Object Detection using Region based Convolutional Neural Network: A Survey International Journal for Research in Applied Science & Engineering Technology (IJRASET), ISSN: 2321-9653 Volume 8 Issue VII July 2020 by Rekha B. S, Dr. G N Srinivasan, Chandana EP\, Achala N Gowda.
  4. Artificial Neural Network Systems, International Journal of Imaging and Robotics, ISSN: 0974-0627, Vol 21, Iss 2, 2021. By Roza Dastres and Mohsen Soori.
  5. Generative Adversarial Nets, by Ian J. Goodfellow, Jean Pouget-Abadie , Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair , Aaron Courville, Yoshua Bengio, https://arxiv.org/pdf/1406.2661.pdf .
  6. Online Deep Learning based on Auto-Encoder, Si-si Zhanga , Jian-wei Liua,∗ , Xin Zuoa , Run-kun Lua , Si-ming Liana.
  7. A Gentle Introduction to Reinforcement learning and its application in different fields IEEE Access, Volume 8, 2020, Muddasar Naeem, Syed Tahir Hussain Rizvi, And Antonio Coronato.
  8. https://github.com/deep-reinforcement-learning-book/Chapter4-DQN.
  9. Rashmi Bisht, Ritu Vijay , and Shweta Singh “Comparative Analysis of Fixed Valued Impulse Noise Removal Techniques for Image Enhancement” Springer Nature Singapore Pte Ltd. 2018 M. Singh et al. (Eds.): ICACDS 2018, CCIS 905, pp. 175–184, 2018.
  10. https://www.researchgate.net/publication/347564769_image_segmentation_techniques
  11. Chinmoy Ghosh, Suman Majumder, Sangram Ray, Shrayasi Datta, and Satyendra Nath Mandal “Different EDGE Detection Techniques: A Review” Springer Nature Singapore Pte Ltd. 2020.
  12. Thippanna, G. Suresh, Y. Hema, Dr. T. Bhaskar Reddy “a re-examine of gen on an assortment of images, compression techniques and its algorithms”. International Journal of Advanced Research in Computer Science. Nov/Dec2012, Vol. 3 Issue 6, p112-119.
  13. Ravi S , A M Khan “Morphological Operations for Image Processing : Understanding and its Applications”, NCVSComs-13 CONFERENCE PROCEEDINGS on 19 February 2015.
  14. https://www.slideshare.net/mathupuji/digital-image-processing-image-restoration
  15. https://kdkce.edu.in/writereaddata/fckimagefile/DIP%20Unit%206%20Vijay%20Chakole_1.pdf
  16. Swapan Kumar Haldar, Chapter 3: Photogeology, Remote Sensing, and Geographic Information System in Mineral Exploration, 2018, P 47-68
  17. Shyam G. Dafe1, Shubham S. Chavhan2, Optical Character Recognition Using Image Processing in International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056, Volume: 05 Issue: 03 | Mar-2018, p: 962- 964.
  18. https://www.researchgate.net/publication/331993919_Image_Classification.
Index Terms

Computer Science
Information Sciences

Keywords

Image Processing Convolution Neural Networks (CNNs) Long Short Term Memory Networks Recurrent Neural Networks (RNNs) Deep Belief Networks Restricted Boltzmann Machines