Zobrazeno 1 - 10
of 200
pro vyhledávání: '"Konovalov, Dmitry"'
Autor:
Konovalov, Dmitry A.
The Mars Spectrometry 2: Gas Chromatography challenge was sponsored by NASA and run on the DrivenData competition platform in 2022. This report describes the solution which achieved the second-best score on the competition's test dataset. The solutio
Externí odkaz:
http://arxiv.org/abs/2403.15990
Autor:
Knutsen, Espen M.1,2 (AUTHOR) espen.knutsen@jcu.edu.au, Konovalov, Dmitry A.1 (AUTHOR)
Publikováno v:
Scientific Reports. 9/9/2024, Vol. 14 Issue 1, p1-8. 8p.
Autor:
Konovalov, Dmitry I., Novikova, Evgeniya D., Ivanov, Anton A., Yanshole, Vadim V., Kuratieva, Natalia V., Berezin, Alexey S., Shestopalov, Michael A.
Publikováno v:
In Polyhedron 15 March 2024 251
Autor:
Saleh, Alzayat, Laradji, Issam H., Konovalov, Dmitry A., Bradley, Michael, Vazquez, David, Sheaves, Marcus
Visual analysis of complex fish habitats is an important step towards sustainable fisheries for human consumption and environmental protection. Deep Learning methods have shown great promise for scene analysis when trained on large-scale datasets. Ho
Externí odkaz:
http://arxiv.org/abs/2008.12603
Akademický článek
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Deep learning Convolutional Neural Network (CNN) models are powerful classification models but require a large amount of training data. In niche domains such as bird acoustics, it is expensive and difficult to obtain a large number of training sample
Externí odkaz:
http://arxiv.org/abs/1909.07526
Approximately 2,500 weights and corresponding images of harvested Lates calcarifer (Asian seabass or barramundi) were collected at three different locations in Queensland, Australia. Two instances of the LinkNet-34 segmentation Convolutional Neural N
Externí odkaz:
http://arxiv.org/abs/1909.02710
Autor:
Efremova, Dina B., Konovalov, Dmitry A., Siriapisith, Thanongchai, Kusakunniran, Worapan, Haddawy, Peter
Automatic segmentation of hepatic lesions in computed tomography (CT) images is a challenging task to perform due to heterogeneous, diffusive shape of tumors and complex background. To address the problem more and more researchers rely on assistance
Externí odkaz:
http://arxiv.org/abs/1908.01279
Publikováno v:
2018 Digital Image Computing: Techniques and Applications (DICTA), Canberra, Australia, 2018, pp. 1-7
Cane toads are invasive, toxic to native predators, compete with native insectivores, and have a devastating impact on Australian ecosystems, prompting the Australian government to list toads as a key threatening process under the Environment Protect
Externí odkaz:
http://arxiv.org/abs/1906.03547
Autor:
Konovalov, Dmitry A., Saleh, Alzayat, Bradley, Michael, Sankupellay, Mangalam, Marini, Simone, Sheaves, Marcus
Publikováno v:
2019 International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, 2019, pp. 1-8
Given a sufficiently large training dataset, it is relatively easy to train a modern convolution neural network (CNN) as a required image classifier. However, for the task of fish classification and/or fish detection, if a CNN was trained to detect o
Externí odkaz:
http://arxiv.org/abs/1905.10708