Matches in SemOpenAlex for { <https://semopenalex.org/work/W4327499827> ?p ?o ?g. }
Showing items 1 to 85 of
85
with 100 items per page.
- W4327499827 abstract "Communication is a major part of life. For people who are deaf and dumb, sign language is imperative. All sign languages contain various hand movements and finger placement which in turn form different gestures. Learning any sign language can be challenging. With the current number of different sign languages available around the world, it makes it very hard for people to use sign languages for communication without the help of a translator. Out of all the sign languages available around the world American Sign Language is used by many. Engineers and researchers around the world have been working with different machine learning algorithms to build a better system which can either be only software or along with hardware. The smart gloves have so far been the most effective hardware with machine learning software developed till now as compared to a camera. These smart gloves can be developed using TinyML with the Convolutional Neural Network (CNN) algorithm for best accuracy with low footprint. This comprehensive literature review goes into the details of the different algorithms explored for sign language recognition, the existing systems, and the proposed system using Raspberry Pi Pico." @default.
- W4327499827 created "2023-03-17" @default.
- W4327499827 creator A5021496750 @default.
- W4327499827 creator A5039103442 @default.
- W4327499827 creator A5044031917 @default.
- W4327499827 creator A5056680014 @default.
- W4327499827 creator A5083430919 @default.
- W4327499827 date "2022-12-26" @default.
- W4327499827 modified "2023-10-16" @default.
- W4327499827 title "Survey on implementation of TinyML for real-time sign language recognition using smart gloves" @default.
- W4327499827 cites W2087293868 @default.
- W4327499827 cites W2094308143 @default.
- W4327499827 cites W2329366289 @default.
- W4327499827 cites W2473710204 @default.
- W4327499827 cites W2504094420 @default.
- W4327499827 cites W2507657305 @default.
- W4327499827 cites W2519166277 @default.
- W4327499827 cites W2549292289 @default.
- W4327499827 cites W2602538865 @default.
- W4327499827 cites W2902048647 @default.
- W4327499827 cites W2916310629 @default.
- W4327499827 cites W3013354800 @default.
- W4327499827 cites W3030990843 @default.
- W4327499827 cites W3087439305 @default.
- W4327499827 cites W3126481461 @default.
- W4327499827 cites W4223949488 @default.
- W4327499827 cites W4285301480 @default.
- W4327499827 cites W4296341526 @default.
- W4327499827 doi "https://doi.org/10.1109/icerect56837.2022.10060135" @default.
- W4327499827 hasPublicationYear "2022" @default.
- W4327499827 type Work @default.
- W4327499827 citedByCount "1" @default.
- W4327499827 countsByYear W43274998272023 @default.
- W4327499827 crossrefType "proceedings-article" @default.
- W4327499827 hasAuthorship W4327499827A5021496750 @default.
- W4327499827 hasAuthorship W4327499827A5039103442 @default.
- W4327499827 hasAuthorship W4327499827A5044031917 @default.
- W4327499827 hasAuthorship W4327499827A5056680014 @default.
- W4327499827 hasAuthorship W4327499827A5083430919 @default.
- W4327499827 hasConcept C134306372 @default.
- W4327499827 hasConcept C138885662 @default.
- W4327499827 hasConcept C139676723 @default.
- W4327499827 hasConcept C154945302 @default.
- W4327499827 hasConcept C159437735 @default.
- W4327499827 hasConcept C199360897 @default.
- W4327499827 hasConcept C207347870 @default.
- W4327499827 hasConcept C2776737515 @default.
- W4327499827 hasConcept C2777904410 @default.
- W4327499827 hasConcept C28490314 @default.
- W4327499827 hasConcept C33923547 @default.
- W4327499827 hasConcept C41008148 @default.
- W4327499827 hasConcept C41895202 @default.
- W4327499827 hasConcept C522192633 @default.
- W4327499827 hasConcept C81363708 @default.
- W4327499827 hasConceptScore W4327499827C134306372 @default.
- W4327499827 hasConceptScore W4327499827C138885662 @default.
- W4327499827 hasConceptScore W4327499827C139676723 @default.
- W4327499827 hasConceptScore W4327499827C154945302 @default.
- W4327499827 hasConceptScore W4327499827C159437735 @default.
- W4327499827 hasConceptScore W4327499827C199360897 @default.
- W4327499827 hasConceptScore W4327499827C207347870 @default.
- W4327499827 hasConceptScore W4327499827C2776737515 @default.
- W4327499827 hasConceptScore W4327499827C2777904410 @default.
- W4327499827 hasConceptScore W4327499827C28490314 @default.
- W4327499827 hasConceptScore W4327499827C33923547 @default.
- W4327499827 hasConceptScore W4327499827C41008148 @default.
- W4327499827 hasConceptScore W4327499827C41895202 @default.
- W4327499827 hasConceptScore W4327499827C522192633 @default.
- W4327499827 hasConceptScore W4327499827C81363708 @default.
- W4327499827 hasLocation W43274998271 @default.
- W4327499827 hasOpenAccess W4327499827 @default.
- W4327499827 hasPrimaryLocation W43274998271 @default.
- W4327499827 hasRelatedWork W2296420732 @default.
- W4327499827 hasRelatedWork W2487791595 @default.
- W4327499827 hasRelatedWork W2903018492 @default.
- W4327499827 hasRelatedWork W2907599639 @default.
- W4327499827 hasRelatedWork W3086971787 @default.
- W4327499827 hasRelatedWork W3126290060 @default.
- W4327499827 hasRelatedWork W3205017362 @default.
- W4327499827 hasRelatedWork W4312222638 @default.
- W4327499827 hasRelatedWork W4313444768 @default.
- W4327499827 hasRelatedWork W4380047643 @default.
- W4327499827 isParatext "false" @default.
- W4327499827 isRetracted "false" @default.
- W4327499827 workType "article" @default.