Sidescan sonar images for training automated recognition of submerged body-like objects

1467 48 18503 4 73129 document 18503 sidescan_sonar_images_PRIME_CNN_training.zip application/zip 63f683abfa1dc0a91339cd576ac47858 MD5 6165203835 2024-10-28 13:24:19 https://researchdata.bath.ac.uk/1467/1/sidescan_sonar_images_PRIME_CNN_training.zip 1467 1 1 application/zip other en public cc_by

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data 18507 2 73197 document 18507 README.txt text/plain 1147638250062605062a5511c3ecaf22 MD5 1421 2024-10-30 16:59:44 https://researchdata.bath.ac.uk/1467/2/README.txt 1467 2 2 text/plain other en public cc_by

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documentation 18508 1 73201 document 18508 indexcodes.txt text/plain 04595cd2fb0260db6b2cc0b17394e71c MD5 735 2024-10-30 18:11:08 https://researchdata.bath.ac.uk/1467/3/indexcodes.txt 1467 3 3 text/plain other Generate index codes conversion from other to indexcodes en public

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http://eprints.org/relation/isVersionOf https://researchdata.bath.ac.uk/id/document/18507 http://eprints.org/relation/isVolatileVersionOf https://researchdata.bath.ac.uk/id/document/18507 http://eprints.org/relation/isIndexCodesVersionOf https://researchdata.bath.ac.uk/id/document/18507 archive 1816 disk0/00/00/14/67 2024-10-31 10:37:26 2024-11-02 05:52:17 2024-10-31 10:37:26 data_collection show Rymansaib Zuhayr Z.Rymansaib@bath.ac.uk 0000-0001-7256-3820 University of Bath FALSE Nga Yan yzn21@bath.edu University of Bath FALSE Anthony Treloar Alfie A.O.Anthony.Treloar@bath.ac.uk 0000-0002-8119-9765 University of Bath FALSE Hunter Alan A.J.Hunter@bath.ac.uk 0000-0003-2887-5442 University of Bath FALSE Sidescan sonar images for training automated recognition of submerged body-like objects FB0110 dept_mech_eng police, search and rescue, sonar imaging, automated target recognition, deep learning, CNN This dataset contains sonar image data collected from various locations in Bath and Bristol, UK. It was collected using an autonomous uncrewed surface vessel (USV) equipped with Blueprint Subsea StarFish 450 and StarFish 990 side scanning sonar. The higher resolution images were used to train convolutional neural networks (CNNs) for autonomous detection of a sunken mannequin, used as a proxy for a drowning victim in missing persons scenarios. 2024-10-30 University of Bath public RightsHolder University of Bath Engineering and Physical Sciences Research Council https://doi.org/10.13039/501100000266 EP/X030156/1 Human-Machine Learning of Ambiguities to Support Safe, Effective, and Legal Decision Making adm Full details of the methodology used to collect the images using side scanning sonar may be found in the paper, "A prototype autonomous robot for underwater crime scene investigation and emergency response". https://doi.org/10.1002/rob.22164 2017-10-05 2022-04-08 Kennet and Avon Canal, UK. Minerva Bath Rowing Club, Bath, UK. Underfall Yard, Bristol, UK. en 1 10.15125/BATH-01467 https://doi.org/10.3390/rs16214036 pub https://doi.org/10.1002/rob.22164 pub open We request that any users of this dataset please cite the two associated articles: Rymansaib, Z., Thomas, B., Treloar, A. A., Metcalfe, B., Wilson, P., and Hunter, A., 2023. A prototype autonomous robot for underwater crime scene investigation and emergency response. Journal of Field Robotics, 40(5), 983-1002. Available from: https://doi.org/10.1002/rob.22164. Nga, Y. Z., Rymansaib, Z., Anthony Treloar, A., and Hunter, A., 2024. Automated Recognition of Submerged Body-like Objects in Sonar Images Using Convolutional Neural Networks. In: Remote Sensing, 4036. Available from: https://doi.org/10.3390/rs16214036.