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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

Issue per Year : 12

Volume Published : 8

Issue Published : 88

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Paper Title: Underwater Object Detection Based On Improved CNN
Authors Name: Nagaveni B Nimbal , Samrudh R , Rakshitha M V , Prakruthi P S
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Published Paper Id: IJRTI2301001
Published In: Volume 8 Issue 1, January-2023
Abstract: Detection and analyzing underwater noise is crucial for companies working in the marine industry. The CNN model employs single forward propagation through a neural network to detect objects in real time, that is the entire image is predicted in a single algorithm run for training and validation. Thus, to overcome the overfitting problem due to these inherent problems in the domain-specific dataset,CNN model pre-trained by the public image dataset is usually adopted for its fine-tuning. For example, an autonomous ship equipped with an Automatic Identification System (AIS) requires safe navigation , which is achieved by the detection of surrounding objects. Therefore, this study aimed to develop a new optimized model using one of the network architectures for deep learning features that would learn automatically from the input data, eliminating the requirements and engineering effort. Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data. In this work, we propose a solution for underwater object detection that uses a combination of Convolutional Neural Network and specific image pre-processing steps. The goal is to classify underwater objects into biodegradable and non-biodegradable.
Keywords: Detecting underwater object and classifying objects into Biodegradable or Non biodegradable..
Cite Article: "Underwater Object Detection Based On Improved CNN", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 1, page no.1 - 3, January-2023, Available :http://www.ijrti.org/papers/IJRTI2301001.pdf
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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: IJRTI2301001
Registration ID:184883
Published In: Volume 8 Issue 1, January-2023
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Page No: 1 - 3
Country: Bangalore, Karnataka, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2301001
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2301001
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

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