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Call for Papers:Vol.11 Issue.3

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Title: :  DETECTION AND EXTRACTION OF SEA MINES USING CNN
PaperId: :  17637
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 8 Issue 3 2022
DUI:    16.0415/IJARIIE-17637
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Sheethal SVidyavardhaka College of Engineering
Kiran GVidyavardhaka College of Engineering
Soundarya SVidyavardhaka College of Engineering
Vidhisha VVidyavardhaka College of Engineering

Abstract

Information Science and Engineering
FRCNN, Neural network, Image processing, Deep Learning, ResNet, TensorFlow, Python
The Conventional worry of navel asset is naval mines; these mines are stationary and were planted during war times and now they have been working as a threat to naval ships, and submarines. Detection of those naval mines has been one of the foremost risk-taking tasks, with modern technology various techniques are wont to detect these mines Using Ultrasonic signals, Symbolic pattern analysis of side-scan sonar images but detection through image processing has been one of the most challenging and efficient ones since it can solve the real-time problem with less error, the image classification model like uses FRCNN(Fast Region Convolutional Neural Network) algorithm to classify the objects as mine or not. The cloud platform is employed to watch the mine and as soon as the changes are observed the Android application will reflect the changes.

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IJARIIE Sheethal S, Kiran G, Soundarya S, and Vidhisha V. "DETECTION AND EXTRACTION OF SEA MINES USING CNN" International Journal Of Advance Research And Innovative Ideas In Education Volume 8 Issue 3 2022 Page 5487-5495
MLA Sheethal S, Kiran G, Soundarya S, and Vidhisha V. "DETECTION AND EXTRACTION OF SEA MINES USING CNN." International Journal Of Advance Research And Innovative Ideas In Education 8.3(2022) : 5487-5495.
APA Sheethal S, Kiran G, Soundarya S, & Vidhisha V. (2022). DETECTION AND EXTRACTION OF SEA MINES USING CNN. International Journal Of Advance Research And Innovative Ideas In Education, 8(3), 5487-5495.
Chicago Sheethal S, Kiran G, Soundarya S, and Vidhisha V. "DETECTION AND EXTRACTION OF SEA MINES USING CNN." International Journal Of Advance Research And Innovative Ideas In Education 8, no. 3 (2022) : 5487-5495.
Oxford Sheethal S, Kiran G, Soundarya S, and Vidhisha V. 'DETECTION AND EXTRACTION OF SEA MINES USING CNN', International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, 2022, p. 5487-5495. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/DETECTION_AND_EXTRACTION_OF_SEA_MINES_USING_CNN_ijariie17637.pdf (Accessed : ).
Harvard Sheethal S, Kiran G, Soundarya S, and Vidhisha V. (2022) 'DETECTION AND EXTRACTION OF SEA MINES USING CNN', International Journal Of Advance Research And Innovative Ideas In Education, 8(3), pp. 5487-5495IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/DETECTION_AND_EXTRACTION_OF_SEA_MINES_USING_CNN_ijariie17637.pdf (Accessed : )
IEEE Sheethal S, Kiran G, Soundarya S, and Vidhisha V, "DETECTION AND EXTRACTION OF SEA MINES USING CNN," International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, pp. 5487-5495, May-Jun 2022. [Online]. Available: https://ijariie.com/AdminUploadPdf/DETECTION_AND_EXTRACTION_OF_SEA_MINES_USING_CNN_ijariie17637.pdf [Accessed : ].
Turabian Sheethal S, Kiran G, Soundarya S, and Vidhisha V. "DETECTION AND EXTRACTION OF SEA MINES USING CNN." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 8 number 3 ().
Vancouver Sheethal S, Kiran G, Soundarya S, and Vidhisha V. DETECTION AND EXTRACTION OF SEA MINES USING CNN. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2022 [Cited : ]; 8(3) : 5487-5495. Available from: https://ijariie.com/AdminUploadPdf/DETECTION_AND_EXTRACTION_OF_SEA_MINES_USING_CNN_ijariie17637.pdf
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