Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy
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https://hdl.handle.net/10037/30820Date
2023-06-03Type
Journal articleTidsskriftartikkel
Peer reviewed
Author
Wickstrøm, Kristoffer; Løkse, Sigurd Eivindson; Kampffmeyer, Michael; Yu, Shujian; Príncipe, José C.; Jenssen, RobertAbstract
The aquaculture industry is expanding to meet the daily requirements of humanity from high-quality seafood. In
this regard, intensive aquaculture systems are suggested, resulting in high production but being challenged with
immunosuppression and disease invaders. Antibiotics were used for a long time to protect and treat aquatic
animals; however, continuous use led to severe food safety issues, reducing the natural immunity response and
high resistance to harmful bacterial strains. Therefore, natural functional additives were introduced to reduce or
even replace chemotherapies. More specifically, marine-derived substances showed effective immunostimulant
and antioxidative roles when introduced to aquatic animals. Bioactive molecules derived from algae, crustaceans, and fish, including astaxanthin, carotenoids, chitosan, fucoidan, lectins, and polyunsaturated fatty acids
(PUFAs), are the most applied additives in aquaculture. In addition, marine-derived biomolecules were introduced to several other sectors, such as nutraceuticals, pharmaceuticals, cosmetics, and agriculture. Marinederived substances are lipid-soluble biomolecules known for their ability to cross the cellular membranes,
thereby causing pigmentation roles. Consequently, marine-derived biomolecules are involved in antioxidative
and immune activation effects and, thereby, high performances and productivity of aquatic animals. In the
literature, there are available knowledge about the possibility of using marine-derived biomolecules in aquaculture. This article presents information about the sources, mode of action, and effects of marine-derived biomolecules on aquatic animals to fortify the scientific community with enough details about friendly natural
substances for sustainable aquaculture.
Publisher
MDPICitation
Wickstrøm, Løkse, Kampffmeyer, Yu, Príncipe, Jenssen. Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy. Entropy. 2023;25(6)Metadata
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