Matches in SemOpenAlex for { <https://semopenalex.org/work/W4316658927> ?p ?o ?g. }
Showing items 1 to 72 of
72
with 100 items per page.
- W4316658927 abstract "Due to the extremely dark nature of the sea's inner water and the fish's quick movement, classifying fish species from images obtained from the ocean presents significant challenges. This article describes an automated approach for identifying and classifying fish species using the deep learning method. It benefits marine scientists in various ways, most notably by allowing for the accurate monitoring of fish reproduction, development, and marine changes. AlexNet, a popular deep convolutional neural network model, is employed in this proposed study to classify fish species. This research modifies the traditional alexnet design to improve the accuracy of fish classification. In this proposed AlexNet architecture, five convolutional layers are used for an efficient texture and color feature extraction process. In addition, three fully connected layers are used for feature selection and classification. Finally, the classification efficiency of the proposed fish species classification system has been proven by comparative analysis with the most popular deep learning models (Alexnet, GoogleNet and VGGNet). The overall performance of the proposed deep learning model is 94%, its sensitivity is 95%, and its specificity is 95.5%, respectively." @default.
- W4316658927 created "2023-01-17" @default.
- W4316658927 creator A5056007834 @default.
- W4316658927 creator A5057478794 @default.
- W4316658927 date "2022-12-01" @default.
- W4316658927 modified "2023-09-27" @default.
- W4316658927 title "An Automated Fish Species Classification System Using Improved Alexnet Model" @default.
- W4316658927 cites W2127692403 @default.
- W4316658927 cites W2291140369 @default.
- W4316658927 cites W2323984227 @default.
- W4316658927 cites W2395530746 @default.
- W4316658927 cites W2594982232 @default.
- W4316658927 cites W2746325398 @default.
- W4316658927 cites W2904637289 @default.
- W4316658927 cites W2963246747 @default.
- W4316658927 cites W2966151507 @default.
- W4316658927 cites W3046202023 @default.
- W4316658927 cites W3092059570 @default.
- W4316658927 cites W3146159142 @default.
- W4316658927 doi "https://doi.org/10.1109/iceca55336.2022.10009302" @default.
- W4316658927 hasPublicationYear "2022" @default.
- W4316658927 type Work @default.
- W4316658927 citedByCount "0" @default.
- W4316658927 crossrefType "proceedings-article" @default.
- W4316658927 hasAuthorship W4316658927A5056007834 @default.
- W4316658927 hasAuthorship W4316658927A5057478794 @default.
- W4316658927 hasConcept C108583219 @default.
- W4316658927 hasConcept C115961682 @default.
- W4316658927 hasConcept C138885662 @default.
- W4316658927 hasConcept C148483581 @default.
- W4316658927 hasConcept C153180895 @default.
- W4316658927 hasConcept C154945302 @default.
- W4316658927 hasConcept C2776401178 @default.
- W4316658927 hasConcept C2909208804 @default.
- W4316658927 hasConcept C41008148 @default.
- W4316658927 hasConcept C41895202 @default.
- W4316658927 hasConcept C505870484 @default.
- W4316658927 hasConcept C52622490 @default.
- W4316658927 hasConcept C75294576 @default.
- W4316658927 hasConcept C81363708 @default.
- W4316658927 hasConcept C86803240 @default.
- W4316658927 hasConceptScore W4316658927C108583219 @default.
- W4316658927 hasConceptScore W4316658927C115961682 @default.
- W4316658927 hasConceptScore W4316658927C138885662 @default.
- W4316658927 hasConceptScore W4316658927C148483581 @default.
- W4316658927 hasConceptScore W4316658927C153180895 @default.
- W4316658927 hasConceptScore W4316658927C154945302 @default.
- W4316658927 hasConceptScore W4316658927C2776401178 @default.
- W4316658927 hasConceptScore W4316658927C2909208804 @default.
- W4316658927 hasConceptScore W4316658927C41008148 @default.
- W4316658927 hasConceptScore W4316658927C41895202 @default.
- W4316658927 hasConceptScore W4316658927C505870484 @default.
- W4316658927 hasConceptScore W4316658927C52622490 @default.
- W4316658927 hasConceptScore W4316658927C75294576 @default.
- W4316658927 hasConceptScore W4316658927C81363708 @default.
- W4316658927 hasConceptScore W4316658927C86803240 @default.
- W4316658927 hasLocation W43166589271 @default.
- W4316658927 hasOpenAccess W4316658927 @default.
- W4316658927 hasPrimaryLocation W43166589271 @default.
- W4316658927 hasRelatedWork W2592385986 @default.
- W4316658927 hasRelatedWork W2732542196 @default.
- W4316658927 hasRelatedWork W2760085659 @default.
- W4316658927 hasRelatedWork W2800691917 @default.
- W4316658927 hasRelatedWork W2940977206 @default.
- W4316658927 hasRelatedWork W2969680539 @default.
- W4316658927 hasRelatedWork W3011074480 @default.
- W4316658927 hasRelatedWork W3156786002 @default.
- W4316658927 hasRelatedWork W4307883119 @default.
- W4316658927 hasRelatedWork W564581980 @default.
- W4316658927 isParatext "false" @default.
- W4316658927 isRetracted "false" @default.
- W4316658927 workType "article" @default.