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Volumn , Issue , 2018, Pages

Looking for seagrass: Deep learning for visual coverage estimation

Author keywords

[No Author keywords available]

Indexed keywords

DEEP NEURAL NETWORKS; IMAGE SEGMENTATION; NEURAL NETWORKS; OCEANOGRAPHY; VIDEO RECORDING;

EID: 85060315426     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/OCEANSKOBE.2018.8559302     Document Type: Conference Paper
Times cited : (31)

References (17)
  • 1
    • 84916885727 scopus 로고    scopus 로고
    • Monitoring of seagrass by lightweight auv: A posidonia oceanica case study surrounding murter island of Croatia
    • June
    • A. Vasilijevic, N. Miskovic, Z. Vukic, and F. Mandic, “Monitoring of seagrass by lightweight auv: A posidonia oceanica case study surrounding murter island of croatia,” in 22nd Mediterranean Conference on Control and Automation, June 2014, pp. 758–763.
    • (2014) 22nd Mediterranean Conference on Control and Automation , pp. 758-763
    • Vasilijevic, A.1    Miskovic, N.2    Vukic, Z.3    Mandic, F.4
  • 4
    • 85032696042 scopus 로고    scopus 로고
    • Visual discrimination and large area mapping of posidonia oceanica using a lightweight auv
    • F. Bonin-Font, A. Burguera, and J. L. Lisani, “Visual discrimination and large area mapping of posidonia oceanica using a lightweight auv,” IEEE Access, vol. PP, no. 99, pp. 1–1, 2017.
    • (2017) IEEE Access , vol.PP , Issue.99 , pp. 1
    • Bonin-Font, F.1    Burguera, A.2    Lisani, J.L.3
  • 5
    • 85044779915 scopus 로고    scopus 로고
    • Machine learning and deep learning strategies to identify posidonia meadows in underwater images
    • June
    • Y. Gonzalez-Cid, A. Burguera, F. Bonin-Font, and A. Matamoros, “Machine learning and deep learning strategies to identify posidonia meadows in underwater images,” in OCEANS 2017 - Aberdeen, June 2017, pp. 1–5.
    • (2017) OCEANS 2017 - Aberdeen , pp. 1-5
    • Gonzalez-Cid, Y.1    Burguera, A.2    Bonin-Font, F.3    Matamoros, A.4
  • 7
    • 84919904909 scopus 로고    scopus 로고
    • Compact watershed and preemptive slic: On improving trade-offs of superpixel segmentation algorithms
    • Aug
    • P. Neubert and P. Protzel, “Compact watershed and preemptive slic: On improving trade-offs of superpixel segmentation algorithms,” in 2014 22nd International Conference on Pattern Recognition, Aug 2014, pp. 996–1001.
    • (2014) 2014 22nd International Conference on Pattern Recognition , pp. 996-1001
    • Neubert, P.1    Protzel, P.2
  • 9
    • 34247557079 scopus 로고    scopus 로고
    • Dynamic texture recognition using local binary patterns with an application to facial expressions
    • June
    • G. Zhao and M. Pietikainen, “Dynamic texture recognition using local binary patterns with an application to facial expressions,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 6, pp. 915–928, June 2007.
    • (2007) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.29 , Issue.6 , pp. 915-928
    • Zhao, G.1    Pietikainen, M.2
  • 10
    • 84906504048 scopus 로고    scopus 로고
    • Decaf: A deep convolutional activation feature for generic visual recognition
    • abs/1310.1531
    • J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, and T. Darrell, “Decaf: A deep convolutional activation feature for generic visual recognition,” CoRR, vol. abs/1310.1531, 2013.
    • (2013) CoRR
    • Donahue, J.1    Jia, Y.2    Vinyals, O.3    Hoffman, J.4    Zhang, N.5    Tzeng, E.6    Darrell, T.7
  • 14
    • 84995625580 scopus 로고    scopus 로고
    • Rethinking the inception architecture for computer vision
    • abs/1512.00567
    • C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna, “Rethinking the inception architecture for computer vision,” CoRR, vol. abs/1512.00567, 2015.
    • (2015) CoRR
    • Szegedy, C.1    Vanhoucke, V.2    Ioffe, S.3    Shlens, J.4    Wojna, Z.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.