Matches in SemOpenAlex for { <https://semopenalex.org/work/W3136759617> ?p ?o ?g. }
Showing items 1 to 97 of
97
with 100 items per page.
- W3136759617 endingPage "012178" @default.
- W3136759617 startingPage "012178" @default.
- W3136759617 abstract "Abstract In deep learning-based object detection, especially in face detection, small target and small face has always been a practical and common difficult problem due to its low resolution, blurred image, less information and more noise. In some applications, sensing image data is hard to collect, leading to limited object detection performance. In this paper, we investigate using a generative adversarial network model to augment data for object detection in images. We use generative adversarial network to generate the diverse objects based on the current image data. An improved generative adversarial network is added in the network and a new loss funtion is applied during the trianing process to generate diverse and high-quality traing images. Experiments show that images generated by generative adversarial network have higher quality than counterparts." @default.
- W3136759617 created "2021-03-29" @default.
- W3136759617 creator A5002569099 @default.
- W3136759617 creator A5005592260 @default.
- W3136759617 creator A5008560050 @default.
- W3136759617 creator A5029772640 @default.
- W3136759617 creator A5042810113 @default.
- W3136759617 date "2021-03-01" @default.
- W3136759617 modified "2023-09-25" @default.
- W3136759617 title "Improved Object Detection using Data Enhancement method based on Generative Adversarial Nets" @default.
- W3136759617 cites W2122992840 @default.
- W3136759617 cites W2148143831 @default.
- W3136759617 cites W2336589871 @default.
- W3136759617 cites W2560920409 @default.
- W3136759617 cites W2806070179 @default.
- W3136759617 cites W2890319410 @default.
- W3136759617 cites W2914626434 @default.
- W3136759617 cites W2914663144 @default.
- W3136759617 cites W2922102451 @default.
- W3136759617 cites W2931068004 @default.
- W3136759617 cites W2964298196 @default.
- W3136759617 doi "https://doi.org/10.1088/1742-6596/1827/1/012178" @default.
- W3136759617 hasPublicationYear "2021" @default.
- W3136759617 type Work @default.
- W3136759617 sameAs 3136759617 @default.
- W3136759617 citedByCount "1" @default.
- W3136759617 countsByYear W31367596172022 @default.
- W3136759617 crossrefType "journal-article" @default.
- W3136759617 hasAuthorship W3136759617A5002569099 @default.
- W3136759617 hasAuthorship W3136759617A5005592260 @default.
- W3136759617 hasAuthorship W3136759617A5008560050 @default.
- W3136759617 hasAuthorship W3136759617A5029772640 @default.
- W3136759617 hasAuthorship W3136759617A5042810113 @default.
- W3136759617 hasBestOaLocation W31367596171 @default.
- W3136759617 hasConcept C111472728 @default.
- W3136759617 hasConcept C111919701 @default.
- W3136759617 hasConcept C115961682 @default.
- W3136759617 hasConcept C119857082 @default.
- W3136759617 hasConcept C138885662 @default.
- W3136759617 hasConcept C144024400 @default.
- W3136759617 hasConcept C153180895 @default.
- W3136759617 hasConcept C154945302 @default.
- W3136759617 hasConcept C167966045 @default.
- W3136759617 hasConcept C2776151529 @default.
- W3136759617 hasConcept C2779304628 @default.
- W3136759617 hasConcept C2779530757 @default.
- W3136759617 hasConcept C2781238097 @default.
- W3136759617 hasConcept C2988773926 @default.
- W3136759617 hasConcept C31972630 @default.
- W3136759617 hasConcept C36289849 @default.
- W3136759617 hasConcept C37736160 @default.
- W3136759617 hasConcept C39890363 @default.
- W3136759617 hasConcept C41008148 @default.
- W3136759617 hasConcept C98045186 @default.
- W3136759617 hasConcept C99498987 @default.
- W3136759617 hasConceptScore W3136759617C111472728 @default.
- W3136759617 hasConceptScore W3136759617C111919701 @default.
- W3136759617 hasConceptScore W3136759617C115961682 @default.
- W3136759617 hasConceptScore W3136759617C119857082 @default.
- W3136759617 hasConceptScore W3136759617C138885662 @default.
- W3136759617 hasConceptScore W3136759617C144024400 @default.
- W3136759617 hasConceptScore W3136759617C153180895 @default.
- W3136759617 hasConceptScore W3136759617C154945302 @default.
- W3136759617 hasConceptScore W3136759617C167966045 @default.
- W3136759617 hasConceptScore W3136759617C2776151529 @default.
- W3136759617 hasConceptScore W3136759617C2779304628 @default.
- W3136759617 hasConceptScore W3136759617C2779530757 @default.
- W3136759617 hasConceptScore W3136759617C2781238097 @default.
- W3136759617 hasConceptScore W3136759617C2988773926 @default.
- W3136759617 hasConceptScore W3136759617C31972630 @default.
- W3136759617 hasConceptScore W3136759617C36289849 @default.
- W3136759617 hasConceptScore W3136759617C37736160 @default.
- W3136759617 hasConceptScore W3136759617C39890363 @default.
- W3136759617 hasConceptScore W3136759617C41008148 @default.
- W3136759617 hasConceptScore W3136759617C98045186 @default.
- W3136759617 hasConceptScore W3136759617C99498987 @default.
- W3136759617 hasIssue "1" @default.
- W3136759617 hasLocation W31367596171 @default.
- W3136759617 hasOpenAccess W3136759617 @default.
- W3136759617 hasPrimaryLocation W31367596171 @default.
- W3136759617 hasRelatedWork W2766091292 @default.
- W3136759617 hasRelatedWork W2774762576 @default.
- W3136759617 hasRelatedWork W2792680412 @default.
- W3136759617 hasRelatedWork W2920645408 @default.
- W3136759617 hasRelatedWork W2950862326 @default.
- W3136759617 hasRelatedWork W2986746197 @default.
- W3136759617 hasRelatedWork W3048537737 @default.
- W3136759617 hasRelatedWork W3120345119 @default.
- W3136759617 hasRelatedWork W4309299543 @default.
- W3136759617 hasRelatedWork W4315926636 @default.
- W3136759617 hasVolume "1827" @default.
- W3136759617 isParatext "false" @default.
- W3136759617 isRetracted "false" @default.
- W3136759617 magId "3136759617" @default.
- W3136759617 workType "article" @default.