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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 Artificial Intelligence and Reliability of Accounting Information Askary, Saeed; Abu-Ghazaleh, Nasser; Tahat, Yasean In: Lecture Notes in Computer Science ; 17th Conference on e-Business, e-Services and e-Society (I3E) ; https://hal.inria.fr/hal-02274162 ; 17th Conference on e-Business, e-Services and e-Society (I3E), Oct 2018, Kuwait City, Kuwait. pp.315-324, ⟨10.1007/978-3-030-02131-3_28⟩ (2018) BASE Show details 2 The 3D indoor deployment in DL-IoT with experimental validation using a particle swarm algorithm based on the dialects of songs Mnasri, Sami; Nasri, Nejah; Val, Thierry In: Proceedings of IWCMC 2018 ; 14th International Wireless Communications and Mobile Computing Conference (IWCMC 2018) ; https://hal.archives-ouvertes.fr/hal-02883831 ; 14th International Wireless Communications and Mobile Computing Conference (IWCMC 2018), Jun 2018, Limassol, Cyprus. pp.928-933, ⟨10.1109/IWCMC.2018.8450473⟩ (2018) BASE Show details 3 Cognitive Architecture and Software Environment for the Design and Experimentation of Survival Behaviors in Artificial Agents Teja Nallapu, Bhargav; Alexandre, Frédéric In: IJCCI 2018 - 10th International Joint Conference on Computational Intelligence ; https://hal.inria.fr/hal-01931497 ; IJCCI 2018 - 10th International Joint Conference on Computational Intelligence, Sep 2018, Seville, Spain (2018) BASE Show details 4 Cognifying Model-Driven Software Engineering Gérard, Sébastien; Cabot, Jordi; Clarisó, Robert... In: Software Technologies: Applications and Foundations ; https://hal-cea.archives-ouvertes.fr/cea-02572650 ; Software Technologies: Applications and Foundations, pp.154-160, 2018, ⟨10.1007/978-3-319-74730-9_13⟩ (2018) BASE Show details 5 Architectures for Real-Time Automatic Sign Language Recognition on Resource-Constrained Device Blair, James M In: UNF Graduate Theses and Dissertations (2018) Abstract: Powerful, handheld computing devices have proliferated among consumers in recent years. Combined with new cameras and sensors capable of detecting objects in three-dimensional space, new gesture-based paradigms of human computer interaction are becoming available. One possible application of these developments is an automated sign language recognition system. This thesis reviews the existing body of work regarding computer recognition of sign language gestures as well as the design of systems for speech recognition, a similar problem. Little work has been done to apply the well-known architectural patterns of speech recognition systems to the domain of sign language recognition. This work creates a functional prototype of such a system, applying three architectures seen in speech recognition systems, using a Hidden Markov classifier with 75-90% accuracy. A thorough search of the literature indicates that no cloud-based system has yet been created for sign language recognition and this is the first implementation of its kind. Accordingly, there have been no empirical performance analyses regarding a cloud-based Automatic Sign Language Recognition (ASLR) system, which this research provides. The performance impact of each architecture, as well as the data interchange format, is then measured based on response time, CPU, memory, and network usage across an increasing vocabulary of sign language gestures. The results discussed herein suggest that a partially-offloaded client-server architecture, where feature extraction occurs on the client device and classification occurs in the cloud, is the ideal selection for all but the smallest vocabularies. Additionally, the results indicate that for the potentially large data sets transmitted for 3D gesture classification, a fast binary interchange protocol such as Protobuf has vastly superior performance to a text-based protocol such as JSON. Keyword: Academic -- UNF -- Computing; Academic -- UNF -- Master of Science in Computer and Information Sciences; architecture; Computer and Systems Architecture; Digital Communications and Networking; Dissertations; mobile; real time; recognition; sign language; Systems and Communications; Thesis; UNF; University of North Florida URL: https://digitalcommons.unf.edu/etd/851 https://digitalcommons.unf.edu/cgi/viewcontent.cgi?article=1893&context=etd BASE Hide details

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