Home > Society & social sciences > Society & culture: general > Object Recognition in Underwater Imaging Using Machine Learning Techniques.
27%
Object Recognition in Underwater Imaging Using Machine Learning Techniques.

Object Recognition in Underwater Imaging Using Machine Learning Techniques.

          
5
4
3
2
1

Out of Stock


Premium quality
Premium quality
Bookswagon upholds the quality by delivering untarnished books. Quality, services and satisfaction are everything for us!
Easy Return
Easy return
Not satisfied with this product! Keep it in original condition and packaging to avail easy return policy.
Certified product
Certified product
First impression is the last impression! Address the book’s certification page, ISBN, publisher’s name, copyright page and print quality.
Secure Checkout
Secure checkout
Security at its finest! Login, browse, purchase and pay, every step is safe and secured.
Money back guarantee
Money-back guarantee:
It’s all about customers! For any kind of bad experience with the product, get your actual amount back after returning the product.
On time delivery
On-time delivery
At your doorstep on time! Get this book delivered without any delay.
Notify me when this book is in stock
Add to Wishlist

About the Book

For many years, mines in the ocean are becoming major worry and threat to human lives and vessel safety. These mines are generally placed in the ocean for security reasons to protect from enemies which can destroy submarines and ship which comes in contact with the mines. It's very difficult to identify and detect the objects in underwater using sonar imagery because of its complications. This is due to factors which involve variations in operational and environment conditions, spatially variable chaos, variation in target shapes, structure and orientation. Considering all these conditions, a method had been proposed which can detect and classify whether the object is a mine or an object which resembles a mine under water. Images are obtained from sonar camera scanner, which is placed in underwater communication network in a moving vehicle with a sensor. In our application, using image processing and machine learning technologies, we have studied the behaviour and differentiate the features of a mines and rocks. In most cases mines are considered to be metal objects. We have designed this application with algorithm which can give a real time capability to detect the objects and distinguish them as seabed objects and imaginary artifacts which are induced by vehicles. UCI dataset is considered in this system which holds all possible attack data with percentage of possibility. This data is then utilized in the pre-processing by applying one hot encoding. Statistical methods are used to obtain Z-scores, mean, median and mode for determining the significant features and training on 80% of dataset is validated. The remaining 20% dataset is tested and validated using Decision tree, K-NN and Gradient boosting algorithm. The efficiency of these algorithms is being analysed and discussed and it is found that Gradient boosting algorithm is best suitable algorithm to be utilized for development of mine detection. Different parameters were interacted based on the testing and checked for false negative rate, accuracy, f-score, precision time. These metrics are vulnerable to the efficiency of the mine detection model that is being proposed.


Best Sellers



Product Details
  • ISBN-13: 9788119549610
  • Publisher: Venkataraman Padmaja
  • Publisher Imprint: Venkataraman Padmaja
  • Height: 229 mm
  • No of Pages: 174
  • Spine Width: 9 mm
  • Width: 152 mm
  • ISBN-10: 8119549619
  • Publisher Date: 31 Aug 2023
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Weight: 240 gr


Similar Products

How would you rate your experience shopping for books on Bookswagon?

Add Photo
Add Photo

Customer Reviews

REVIEWS           
Click Here To Be The First to Review this Product
Object Recognition in Underwater Imaging Using Machine Learning Techniques.
Venkataraman Padmaja -
Object Recognition in Underwater Imaging Using Machine Learning Techniques.
Writing guidlines
We want to publish your review, so please:
  • keep your review on the product. Review's that defame author's character will be rejected.
  • Keep your review focused on the product.
  • Avoid writing about customer service. contact us instead if you have issue requiring immediate attention.
  • Refrain from mentioning competitors or the specific price you paid for the product.
  • Do not include any personally identifiable information, such as full names.

Object Recognition in Underwater Imaging Using Machine Learning Techniques.

Required fields are marked with *

Review Title*
Review
    Add Photo Add up to 6 photos
    Would you recommend this product to a friend?
    Tag this Book
    Read more
    Does your review contain spoilers?
    What type of reader best describes you?
    I agree to the terms & conditions
    You may receive emails regarding this submission. Any emails will include the ability to opt-out of future communications.

    CUSTOMER RATINGS AND REVIEWS AND QUESTIONS AND ANSWERS TERMS OF USE

    These Terms of Use govern your conduct associated with the Customer Ratings and Reviews and/or Questions and Answers service offered by Bookswagon (the "CRR Service").


    By submitting any content to Bookswagon, you guarantee that:
    • You are the sole author and owner of the intellectual property rights in the content;
    • All "moral rights" that you may have in such content have been voluntarily waived by you;
    • All content that you post is accurate;
    • You are at least 13 years old;
    • Use of the content you supply does not violate these Terms of Use and will not cause injury to any person or entity.
    You further agree that you may not submit any content:
    • That is known by you to be false, inaccurate or misleading;
    • That infringes any third party's copyright, patent, trademark, trade secret or other proprietary rights or rights of publicity or privacy;
    • That violates any law, statute, ordinance or regulation (including, but not limited to, those governing, consumer protection, unfair competition, anti-discrimination or false advertising);
    • That is, or may reasonably be considered to be, defamatory, libelous, hateful, racially or religiously biased or offensive, unlawfully threatening or unlawfully harassing to any individual, partnership or corporation;
    • For which you were compensated or granted any consideration by any unapproved third party;
    • That includes any information that references other websites, addresses, email addresses, contact information or phone numbers;
    • That contains any computer viruses, worms or other potentially damaging computer programs or files.
    You agree to indemnify and hold Bookswagon (and its officers, directors, agents, subsidiaries, joint ventures, employees and third-party service providers, including but not limited to Bazaarvoice, Inc.), harmless from all claims, demands, and damages (actual and consequential) of every kind and nature, known and unknown including reasonable attorneys' fees, arising out of a breach of your representations and warranties set forth above, or your violation of any law or the rights of a third party.


    For any content that you submit, you grant Bookswagon a perpetual, irrevocable, royalty-free, transferable right and license to use, copy, modify, delete in its entirety, adapt, publish, translate, create derivative works from and/or sell, transfer, and/or distribute such content and/or incorporate such content into any form, medium or technology throughout the world without compensation to you. Additionally,  Bookswagon may transfer or share any personal information that you submit with its third-party service providers, including but not limited to Bazaarvoice, Inc. in accordance with  Privacy Policy


    All content that you submit may be used at Bookswagon's sole discretion. Bookswagon reserves the right to change, condense, withhold publication, remove or delete any content on Bookswagon's website that Bookswagon deems, in its sole discretion, to violate the content guidelines or any other provision of these Terms of Use.  Bookswagon does not guarantee that you will have any recourse through Bookswagon to edit or delete any content you have submitted. Ratings and written comments are generally posted within two to four business days. However, Bookswagon reserves the right to remove or to refuse to post any submission to the extent authorized by law. You acknowledge that you, not Bookswagon, are responsible for the contents of your submission. None of the content that you submit shall be subject to any obligation of confidence on the part of Bookswagon, its agents, subsidiaries, affiliates, partners or third party service providers (including but not limited to Bazaarvoice, Inc.)and their respective directors, officers and employees.

    Accept

    New Arrivals



    Inspired by your browsing history


    Your review has been submitted!

    You've already reviewed this product!