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1992, Advanced series on ocean engineering, ISBN 9789810204723, Volume 4, xxiii, 324
Book
Marine Geology, ISSN 0025-3227, 10/2016, Volume 380, pp. 44 - 66
Journal Article
Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, 5/2016, Volume 113, Issue 19, pp. 5179 - 5184
Journal Article
Deep-Sea Research Part I, ISSN 0967-0637, 12/2018, Volume 142, pp. 107 - 115
The deep sea has limited food resources and is considered one of the most rigorous environments on Earth. In contrast, zooplankton and their food supply are... 
Trophic position | Ecological stoichiometry | Deep and shallow sea | Trophic niche overlap | TROPICAL NORTH PACIFIC | CARBON | SIZE SPECTRA | FOOD-WEB | HYPERIID AMPHIPODS | ABUNDANCE | SQUID DOSIDICUS-GIGAS | STABLE-ISOTOPE ANALYSIS | OCEANOGRAPHY | DELTA-N-15 | COPEPODS | Comparative analysis | Food supply
Journal Article
Journal Article
Graefe's Archive for Clinical and Experimental Ophthalmology, ISSN 0721-832X, 6/2018, Volume 256, Issue 6, pp. 1151 - 1158
Journal Article
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 5/2019, pp. 1 - 1
radient descent optimization of learning has become a paradigm for training deep convolutional neural networks (DCNN). However, utilizing other learning... 
Training | Deep learning | Mathematical model | Convolutional neural networks | Neurons | Optimization
Journal Article
Pattern Recognition, ISSN 0031-3203, 05/2019, Volume 89, pp. 12 - 21
Nowadays, Convolutional Neural Network (CNN) has achieved great success in various computer vision tasks. However, in classic CNN models, convolution and fully... 
Pre-trained CNN models | Non-linearity in deep learning | Object recognition | Transfer learning | SVM | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Mobile applications | Machine vision | Neural networks | Analysis
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