Matches in SemOpenAlex for { <https://semopenalex.org/work/W4206135013> ?p ?o ?g. }
- W4206135013 abstract "The usability of computer vision is everywhere, whereas deep learning revolutionized the concept of artificial intelligence including computer vision. This paper discusses the leverages of deep learning for computer vision. At first, the background details of computer vision and deep learning have been discussed. Important tasks of computer vision like image classification, object localization, object detection, segmentation are briefly explained. Various types of deep learning algorithms have been described. The architecture of the convolutional neural network has been explained briefly. Applications of deep learning in different fields of computer vision like image classifications, human activity recognition, scene text detection and recognition, object tracking, visual question answering, etc., have been discussed with the references of the recent state-of-the-art works." @default.
- W4206135013 created "2022-01-25" @default.
- W4206135013 creator A5016064028 @default.
- W4206135013 creator A5031593648 @default.
- W4206135013 creator A5075541721 @default.
- W4206135013 creator A5076945527 @default.
- W4206135013 creator A5084662812 @default.
- W4206135013 creator A5086786759 @default.
- W4206135013 date "2021-12-21" @default.
- W4206135013 modified "2023-10-04" @default.
- W4206135013 title "Leveraging Deep Learning for Computer Vision: A Review" @default.
- W4206135013 cites W1936750108 @default.
- W4206135013 cites W1983705368 @default.
- W4206135013 cites W2014481529 @default.
- W4206135013 cites W2025768430 @default.
- W4206135013 cites W2040870580 @default.
- W4206135013 cites W2097117768 @default.
- W4206135013 cites W2108598243 @default.
- W4206135013 cites W2112796928 @default.
- W4206135013 cites W2117731089 @default.
- W4206135013 cites W2129018774 @default.
- W4206135013 cites W2194775991 @default.
- W4206135013 cites W2325939864 @default.
- W4206135013 cites W2549139847 @default.
- W4206135013 cites W2579984156 @default.
- W4206135013 cites W2886810500 @default.
- W4206135013 cites W2887063112 @default.
- W4206135013 cites W2896348597 @default.
- W4206135013 cites W2910683834 @default.
- W4206135013 cites W2919115771 @default.
- W4206135013 cites W2922342173 @default.
- W4206135013 cites W2937742783 @default.
- W4206135013 cites W2941352015 @default.
- W4206135013 cites W2944659700 @default.
- W4206135013 cites W2945385604 @default.
- W4206135013 cites W2949023359 @default.
- W4206135013 cites W2952813363 @default.
- W4206135013 cites W2964878976 @default.
- W4206135013 cites W2966535964 @default.
- W4206135013 cites W2973255917 @default.
- W4206135013 cites W2977942577 @default.
- W4206135013 cites W2990187711 @default.
- W4206135013 cites W2998376881 @default.
- W4206135013 cites W2998784361 @default.
- W4206135013 cites W2999409265 @default.
- W4206135013 cites W3000322757 @default.
- W4206135013 cites W3007219837 @default.
- W4206135013 cites W3016406224 @default.
- W4206135013 cites W3017628311 @default.
- W4206135013 cites W3023846466 @default.
- W4206135013 cites W3035289617 @default.
- W4206135013 cites W3036586801 @default.
- W4206135013 cites W3046404436 @default.
- W4206135013 cites W3048218390 @default.
- W4206135013 cites W3082397598 @default.
- W4206135013 cites W3112119313 @default.
- W4206135013 cites W3130367234 @default.
- W4206135013 cites W3140854437 @default.
- W4206135013 cites W3154571917 @default.
- W4206135013 cites W3162901069 @default.
- W4206135013 cites W3028889242 @default.
- W4206135013 doi "https://doi.org/10.1109/acit53391.2021.9677361" @default.
- W4206135013 hasPublicationYear "2021" @default.
- W4206135013 type Work @default.
- W4206135013 citedByCount "3" @default.
- W4206135013 countsByYear W42061350132022 @default.
- W4206135013 countsByYear W42061350132023 @default.
- W4206135013 crossrefType "proceedings-article" @default.
- W4206135013 hasAuthorship W4206135013A5016064028 @default.
- W4206135013 hasAuthorship W4206135013A5031593648 @default.
- W4206135013 hasAuthorship W4206135013A5075541721 @default.
- W4206135013 hasAuthorship W4206135013A5076945527 @default.
- W4206135013 hasAuthorship W4206135013A5084662812 @default.
- W4206135013 hasAuthorship W4206135013A5086786759 @default.
- W4206135013 hasConcept C107457646 @default.
- W4206135013 hasConcept C108583219 @default.
- W4206135013 hasConcept C154945302 @default.
- W4206135013 hasConcept C170130773 @default.
- W4206135013 hasConcept C2776151529 @default.
- W4206135013 hasConcept C2781238097 @default.
- W4206135013 hasConcept C31972630 @default.
- W4206135013 hasConcept C41008148 @default.
- W4206135013 hasConcept C64876066 @default.
- W4206135013 hasConcept C81363708 @default.
- W4206135013 hasConcept C89600930 @default.
- W4206135013 hasConceptScore W4206135013C107457646 @default.
- W4206135013 hasConceptScore W4206135013C108583219 @default.
- W4206135013 hasConceptScore W4206135013C154945302 @default.
- W4206135013 hasConceptScore W4206135013C170130773 @default.
- W4206135013 hasConceptScore W4206135013C2776151529 @default.
- W4206135013 hasConceptScore W4206135013C2781238097 @default.
- W4206135013 hasConceptScore W4206135013C31972630 @default.
- W4206135013 hasConceptScore W4206135013C41008148 @default.
- W4206135013 hasConceptScore W4206135013C64876066 @default.
- W4206135013 hasConceptScore W4206135013C81363708 @default.
- W4206135013 hasConceptScore W4206135013C89600930 @default.
- W4206135013 hasLocation W42061350131 @default.
- W4206135013 hasOpenAccess W4206135013 @default.
- W4206135013 hasPrimaryLocation W42061350131 @default.
- W4206135013 hasRelatedWork W2019566805 @default.