Author Correction:Deep neural networks for automated detection of marine mammal species (Scientific Reports, (2020), 10, 1, (607), 10.1038/s41598-020-57549-y)
The original version of this Article contained errors. Table 1 omitted to reference the experimental data and its funding sources. As the result, References 78-83 were omitted from Table 1. Added References are listed below: Hatch, Leila T., et al. Quantifying loss of acoustic communication space fo...
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ftunstandrewcris:oai:research-portal.st-andrews.ac.uk:publications/a7d70131-3ed1-4032-8921-18f2da4d83da 2024-06-23T07:51:34+00:00 Author Correction:Deep neural networks for automated detection of marine mammal species (Scientific Reports, (2020), 10, 1, (607), 10.1038/s41598-020-57549-y) Shiu, Yu Palmer, K. J. Roch, Marie A. Fleishman, Erica Liu, Xiaobai Nosal, Eva Marie Helble, Tyler Cholewiak, Danielle Gillespie, Douglas Klinck, Holger 2021-12 https://research-portal.st-andrews.ac.uk/en/researchoutput/author-correction(a7d70131-3ed1-4032-8921-18f2da4d83da).html https://doi.org/10.1038/s41598-021-00460-x http://www.scopus.com/inward/record.url?scp=85117700119&partnerID=8YFLogxK eng eng https://research-portal.st-andrews.ac.uk/en/researchoutput/author-correction(a7d70131-3ed1-4032-8921-18f2da4d83da).html info:eu-repo/semantics/openAccess Shiu , Y , Palmer , K J , Roch , M A , Fleishman , E , Liu , X , Nosal , E M , Helble , T , Cholewiak , D , Gillespie , D & Klinck , H 2021 , ' Author Correction : Deep neural networks for automated detection of marine mammal species (Scientific Reports, (2020), 10, 1, (607), 10.1038/s41598-020-57549-y) ' , Scientific Reports , vol. 11 , no. 1 , 21189 . https://doi.org/10.1038/s41598-021-00460-x article 2021 ftunstandrewcris https://doi.org/10.1038/s41598-021-00460-x10.1038/s41598-020-57549-y 2024-06-13T01:20:25Z The original version of this Article contained errors. Table 1 omitted to reference the experimental data and its funding sources. As the result, References 78-83 were omitted from Table 1. Added References are listed below: Hatch, Leila T., et al. Quantifying loss of acoustic communication space for right whales in and around a US National Marine Sanctuary. Conservation Biology 26.6, 983-994 (2012). Clark, C.W., et al. An ocean observing system for large-scale monitoring and mapping of noise throughout the Stellwagen Bank National Marine Sanctuary. Cornell University, Ithaca, NY (2010). Cholewiak, D., et al. Communicating amidst the noise: modeling the aggregate influence of ambient and vessel noise on baleen whale communication space in a national marine sanctuary. Endangered Species Research, 36, 59-75. (2018). Rice, A. N. et al. Baseline bioacoustic characterization for offshore alternative energy development in North Carolina and Georgia wind planning areas. U.S. Department of the Interior, Bureau of Ocean Energy Management, Gulf of Mexico OCS Region., New Orleans, LA. (2015). Salisbury, D. P., Estabrook, B. J., Klinck, H., & Rice., A. N. Understanding marine mammal presence in the Virginia offshore wind energy area. US Department of the Interior, Bureau of Ocean Energy Management, Sterling, VA. (2019) Bailey, H. et al. Determining offshore use by marine mammals and ambient noise levels using passive acoustic monitoring. U.S. Department of the Interior, Bureau of Ocean Energy Management., Sterling, VA. (2018) Consequently, the legend of Table 1 has been corrected accordingly, “Number of upcalls indicates the number of upcalls annotated by trained analysts. For deployments with two or more recorders, the number of upcalls indicates the total number of upcalls detected across all recorders. Shaded rows indicate data used to train neural networks. Non-shaded rows represent evaluation data. Negative examples for the Kaggle data represent the false detections flagged by the analysts as derived from non-right ... Article in Journal/Newspaper baleen whale University of St Andrews: Research Portal Orleans ENVELOPE(-60.667,-60.667,-63.950,-63.950) Salisbury ENVELOPE(-153.617,-153.617,-85.633,-85.633) |
institution |
Open Polar |
collection |
University of St Andrews: Research Portal |
op_collection_id |
ftunstandrewcris |
language |
English |
description |
The original version of this Article contained errors. Table 1 omitted to reference the experimental data and its funding sources. As the result, References 78-83 were omitted from Table 1. Added References are listed below: Hatch, Leila T., et al. Quantifying loss of acoustic communication space for right whales in and around a US National Marine Sanctuary. Conservation Biology 26.6, 983-994 (2012). Clark, C.W., et al. An ocean observing system for large-scale monitoring and mapping of noise throughout the Stellwagen Bank National Marine Sanctuary. Cornell University, Ithaca, NY (2010). Cholewiak, D., et al. Communicating amidst the noise: modeling the aggregate influence of ambient and vessel noise on baleen whale communication space in a national marine sanctuary. Endangered Species Research, 36, 59-75. (2018). Rice, A. N. et al. Baseline bioacoustic characterization for offshore alternative energy development in North Carolina and Georgia wind planning areas. U.S. Department of the Interior, Bureau of Ocean Energy Management, Gulf of Mexico OCS Region., New Orleans, LA. (2015). Salisbury, D. P., Estabrook, B. J., Klinck, H., & Rice., A. N. Understanding marine mammal presence in the Virginia offshore wind energy area. US Department of the Interior, Bureau of Ocean Energy Management, Sterling, VA. (2019) Bailey, H. et al. Determining offshore use by marine mammals and ambient noise levels using passive acoustic monitoring. U.S. Department of the Interior, Bureau of Ocean Energy Management., Sterling, VA. (2018) Consequently, the legend of Table 1 has been corrected accordingly, “Number of upcalls indicates the number of upcalls annotated by trained analysts. For deployments with two or more recorders, the number of upcalls indicates the total number of upcalls detected across all recorders. Shaded rows indicate data used to train neural networks. Non-shaded rows represent evaluation data. Negative examples for the Kaggle data represent the false detections flagged by the analysts as derived from non-right ... |
format |
Article in Journal/Newspaper |
author |
Shiu, Yu Palmer, K. J. Roch, Marie A. Fleishman, Erica Liu, Xiaobai Nosal, Eva Marie Helble, Tyler Cholewiak, Danielle Gillespie, Douglas Klinck, Holger |
spellingShingle |
Shiu, Yu Palmer, K. J. Roch, Marie A. Fleishman, Erica Liu, Xiaobai Nosal, Eva Marie Helble, Tyler Cholewiak, Danielle Gillespie, Douglas Klinck, Holger Author Correction:Deep neural networks for automated detection of marine mammal species (Scientific Reports, (2020), 10, 1, (607), 10.1038/s41598-020-57549-y) |
author_facet |
Shiu, Yu Palmer, K. J. Roch, Marie A. Fleishman, Erica Liu, Xiaobai Nosal, Eva Marie Helble, Tyler Cholewiak, Danielle Gillespie, Douglas Klinck, Holger |
author_sort |
Shiu, Yu |
title |
Author Correction:Deep neural networks for automated detection of marine mammal species (Scientific Reports, (2020), 10, 1, (607), 10.1038/s41598-020-57549-y) |
title_short |
Author Correction:Deep neural networks for automated detection of marine mammal species (Scientific Reports, (2020), 10, 1, (607), 10.1038/s41598-020-57549-y) |
title_full |
Author Correction:Deep neural networks for automated detection of marine mammal species (Scientific Reports, (2020), 10, 1, (607), 10.1038/s41598-020-57549-y) |
title_fullStr |
Author Correction:Deep neural networks for automated detection of marine mammal species (Scientific Reports, (2020), 10, 1, (607), 10.1038/s41598-020-57549-y) |
title_full_unstemmed |
Author Correction:Deep neural networks for automated detection of marine mammal species (Scientific Reports, (2020), 10, 1, (607), 10.1038/s41598-020-57549-y) |
title_sort |
author correction:deep neural networks for automated detection of marine mammal species (scientific reports, (2020), 10, 1, (607), 10.1038/s41598-020-57549-y) |
publishDate |
2021 |
url |
https://research-portal.st-andrews.ac.uk/en/researchoutput/author-correction(a7d70131-3ed1-4032-8921-18f2da4d83da).html https://doi.org/10.1038/s41598-021-00460-x http://www.scopus.com/inward/record.url?scp=85117700119&partnerID=8YFLogxK |
long_lat |
ENVELOPE(-60.667,-60.667,-63.950,-63.950) ENVELOPE(-153.617,-153.617,-85.633,-85.633) |
geographic |
Orleans Salisbury |
geographic_facet |
Orleans Salisbury |
genre |
baleen whale |
genre_facet |
baleen whale |
op_source |
Shiu , Y , Palmer , K J , Roch , M A , Fleishman , E , Liu , X , Nosal , E M , Helble , T , Cholewiak , D , Gillespie , D & Klinck , H 2021 , ' Author Correction : Deep neural networks for automated detection of marine mammal species (Scientific Reports, (2020), 10, 1, (607), 10.1038/s41598-020-57549-y) ' , Scientific Reports , vol. 11 , no. 1 , 21189 . https://doi.org/10.1038/s41598-021-00460-x |
op_relation |
https://research-portal.st-andrews.ac.uk/en/researchoutput/author-correction(a7d70131-3ed1-4032-8921-18f2da4d83da).html |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1038/s41598-021-00460-x10.1038/s41598-020-57549-y |
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1802642686417567744 |