Konovalov, Dmitry A., Hillcoat, Suzanne, Williams, Genevieve, Birtles, R.
World Journal of Engineering and Technology, 6 (3). Konovalov, Dmitry A., Saleh, Alzayat, Domingos, Jose A., White, Ron D., and Jerry, Dean R.Įstimating mass of harvested Asian seabass Lates calcarifer from images. From: ICAIP 18: 2nd International Conference on Advances in Image Processing, 16-18 June 2018, Chengdu, China. In: Proceedings of the 2nd International Conference on Advances in Image Processing. Konovalov, D.A., Domingos, J.A., White, R.D., and Jerry, D.R. From: DICTA 2019: International Conference on Digital Image Computing: Techniques and Applications, 2-4 December 2019, Perth, WA, Australia. In: Proceedings of the International Conference on Digital Image Computing. Using image processing to automatically measure pearl oyster size for selective breeding. Lapico, Adrian, Sankupellay, Mangalam, Cianciullo, Louis, Myers, Trina, Konovalov, Dmitry A., Jerry, Dean R., Toole, Preston, Jones, David B., and Zenger, Kyall R. From: 2019 IJCNN: International Joint Conference on Neural Networks, 14-19 July 2019, Budapest, Hungary. In: Proceedings of the International Joint Conference on Neural Networks. Underwater fish detection with weak multi-domain supervision. Konovalov, Dmitry A., Saleh, Alzayat, Bradley, Michael, Sankupellay, Mangalam, Marini, Simone, and Sheaves, Marcus Social network analysis of an acoustic environment: the use of visualised data to characterise natural habitats. Wang, Junling, Sankupellay, Mangalam, Konovalov, Dmitry, Towsey, Michael, and Roe, Paul Olsen, Alex, Konovalov, Dmitry A., Philippa, Bronson, Ridd, Peter, Wood, Jake, Johns, Jamie, Banks, Wesley, Girgenti, Benjamin, Kenny, Owen, Whinney, James, Calvert, Brendan, Rahimi Azghadi, Mostafa, and White, Ronald D.ĭeepWeeds: a multiclass weed species image dataset for deep learning.
From: DICTA 2019: International Conference on Digital Image Computing: Techniques and Applications, 2-4 December 2019, Perth, WA, Australia.Įfremova, Dina B., Sankupellay, Mangalam, and Konovalov, Dmitry A.ĭata-efficient classification of birdcall through Convolutional Neural Networks transfer learning. Konovalov, Dmitry A., Saleh, Alzayat, Efremova, Dina B., Domingos, Jose A., and Jerry, Dean R.Īutomatic weight estimation of harvested fish from images. Saleh, Alzayat, Laradji, Issam H., Konovalov, Dmitry A., Bradley, Michael, Vazquez, David, and Sheaves, MarcusĪ realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis. Optimizing video sampling for juvenile fish surveys: using deep learning and evaluation of assumptions to produce critical fisheries parameters.įish and Fisheries, 21 (6). Sheaves, Marcus, Bradley, Michael, Herrera, Cesar, Mattone, Carlo, Lennard, Caitlin, Sheaves, Janine, and Konovalov, Dmitry A. Gulf Coast, 5-30 October 2020, Biloxi, MS, USA. From: Global Oceans 2020: Singapore – U.S. Minke whale detection in underwater imagery using classification CNNs. Alastair, Kusetic, Martha, Adams, Kent, Hillcoat, Suzanne, Curnock, Matthew I., Williams, Genevieve, Sobtzick, Susan, and Sheaves, Marcus Konovalov, Dmitry A., Swinhoe, Natalie, Efremova, Dina B., Birtles, R. Journal of Photochemistry and Photobiology B: Biology, 213.
Keratinocyte skin cancer risks for working school teachers: scenarios and implications of the timing of scheduled duty periods in Queensland, Australia. Alastair, Kusetic, Martha, Hillcoat, Suzanne, Curnock, Matthew I., Williams, Genevieve, and Sheaves, MarcusĪutomatic sorting of Dwarf Minke Whale underwater images.ĭexter, B.R., King, R., Parisi, A.V., Harrison, S.L., Konovalov, D.A., and Downs, N.J. Josi, Dario, Heg, Dik, Takeyama, Tomohiro, Bonfils, Danielle, Konovalov, Dmitry A., Frommen, Joachim G., Kohda, Masanori, and Taborsky, MichaelĪge‐ and sex‐dependent variation in relatedness corresponds to reproductive skew, territory inheritance and workload in cooperatively breeding cichlids.