Matches in SemOpenAlex for { <https://semopenalex.org/work/W4312127970> ?p ?o ?g. }
Showing items 1 to 81 of
81
with 100 items per page.
- W4312127970 endingPage "473" @default.
- W4312127970 startingPage "473" @default.
- W4312127970 abstract "One of the most critical issues that the marine surveillance system has to address is the accuracy of its ship detection. Since it is responsible for identifying potential pirate threats, it has to be able to perform its duties efficiently. In this paper, we present a novel deep learning approach that combines the capabilities of a Graph Neural Network (GNN) and a You Only Look Once (YOLOv7) deep learning framework. The main idea of this method is to provide a better understanding of the ship’s presence in harbor areas. The three hyperparameters that are used in the development of this system are the learning rate, batch sizes, and optimization selection. The results of the experiments show that the Adam optimization achieves a 93.4% success rate when compared to the previous generation of the YOLOv7 algorithm. The High-Resolution Satellite Image Dataset (HRSID), which is a high-resolution image of a synthetic aperture radar, was used for the test. This method can be further improved by taking into account the various kinds of neural network architecture that are commonly used in deep learning." @default.
- W4312127970 created "2023-01-04" @default.
- W4312127970 creator A5025539382 @default.
- W4312127970 creator A5073182926 @default.
- W4312127970 creator A5083631981 @default.
- W4312127970 date "2022-12-12" @default.
- W4312127970 modified "2023-09-28" @default.
- W4312127970 title "Improved Ship Detection Algorithm from Satellite Images Using YOLOv7 and Graph Neural Network" @default.
- W4312127970 cites W2606788270 @default.
- W4312127970 cites W2786644902 @default.
- W4312127970 cites W2788907956 @default.
- W4312127970 cites W2969548447 @default.
- W4312127970 cites W3038948729 @default.
- W4312127970 cites W3146332956 @default.
- W4312127970 cites W3194130996 @default.
- W4312127970 cites W3203054839 @default.
- W4312127970 cites W3204228998 @default.
- W4312127970 cites W4225125287 @default.
- W4312127970 cites W4229012216 @default.
- W4312127970 cites W4283701201 @default.
- W4312127970 doi "https://doi.org/10.3390/a15120473" @default.
- W4312127970 hasPublicationYear "2022" @default.
- W4312127970 type Work @default.
- W4312127970 citedByCount "7" @default.
- W4312127970 countsByYear W43121279702023 @default.
- W4312127970 crossrefType "journal-article" @default.
- W4312127970 hasAuthorship W4312127970A5025539382 @default.
- W4312127970 hasAuthorship W4312127970A5073182926 @default.
- W4312127970 hasAuthorship W4312127970A5083631981 @default.
- W4312127970 hasBestOaLocation W43121279701 @default.
- W4312127970 hasConcept C108583219 @default.
- W4312127970 hasConcept C11413529 @default.
- W4312127970 hasConcept C115961682 @default.
- W4312127970 hasConcept C119857082 @default.
- W4312127970 hasConcept C127413603 @default.
- W4312127970 hasConcept C132525143 @default.
- W4312127970 hasConcept C146978453 @default.
- W4312127970 hasConcept C153180895 @default.
- W4312127970 hasConcept C154945302 @default.
- W4312127970 hasConcept C19269812 @default.
- W4312127970 hasConcept C41008148 @default.
- W4312127970 hasConcept C50644808 @default.
- W4312127970 hasConcept C80444323 @default.
- W4312127970 hasConcept C8642999 @default.
- W4312127970 hasConcept C87360688 @default.
- W4312127970 hasConceptScore W4312127970C108583219 @default.
- W4312127970 hasConceptScore W4312127970C11413529 @default.
- W4312127970 hasConceptScore W4312127970C115961682 @default.
- W4312127970 hasConceptScore W4312127970C119857082 @default.
- W4312127970 hasConceptScore W4312127970C127413603 @default.
- W4312127970 hasConceptScore W4312127970C132525143 @default.
- W4312127970 hasConceptScore W4312127970C146978453 @default.
- W4312127970 hasConceptScore W4312127970C153180895 @default.
- W4312127970 hasConceptScore W4312127970C154945302 @default.
- W4312127970 hasConceptScore W4312127970C19269812 @default.
- W4312127970 hasConceptScore W4312127970C41008148 @default.
- W4312127970 hasConceptScore W4312127970C50644808 @default.
- W4312127970 hasConceptScore W4312127970C80444323 @default.
- W4312127970 hasConceptScore W4312127970C8642999 @default.
- W4312127970 hasConceptScore W4312127970C87360688 @default.
- W4312127970 hasIssue "12" @default.
- W4312127970 hasLocation W43121279701 @default.
- W4312127970 hasLocation W43121279702 @default.
- W4312127970 hasOpenAccess W4312127970 @default.
- W4312127970 hasPrimaryLocation W43121279701 @default.
- W4312127970 hasRelatedWork W3047644063 @default.
- W4312127970 hasRelatedWork W4210794429 @default.
- W4312127970 hasRelatedWork W4223943233 @default.
- W4312127970 hasRelatedWork W4295309597 @default.
- W4312127970 hasRelatedWork W4312200629 @default.
- W4312127970 hasRelatedWork W4323894855 @default.
- W4312127970 hasRelatedWork W4360585206 @default.
- W4312127970 hasRelatedWork W4364306694 @default.
- W4312127970 hasRelatedWork W4380075502 @default.
- W4312127970 hasRelatedWork W4380086463 @default.
- W4312127970 hasVolume "15" @default.
- W4312127970 isParatext "false" @default.
- W4312127970 isRetracted "false" @default.
- W4312127970 workType "article" @default.