An Auto-Encoder Multitask LSTM Model for Boundary Localization

Liu, Yuting; Chen, Jen–Jee; Tseng, Yu–Chee; Li, Frank Y.

doi:10.1109/jsen.2022.3168253

Cited by 6 publications

(1 citation statement)

References 34 publications

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“…The emergence of arti cial intelligence technologies o ers new possibilities to solve this problem. AIoT (Arti cial Intelligence of the Things) combines IoT with AI technologies, thus creating many intelligent applications [2,9,21,25,26,31,38,39].…”

Section: Introductionmentioning

confidence: 99%

An Exchange-based AIoT Platform for Fast AI Application Development

Liang,

Wu,

Tong

et al. 2023

Proceedings of the 19th ACM International Symposium on QoS and Security for Wireless and Mobile Networks

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AIoT is the combination of Internet of Things (IoT) and Articial Intelligence (AI) technologies. While IoT emphasizes more on scalable and e cient communications, AI focuses more on reproducing human capabilities such as recognition and forecasting. An e cient AIoT platform may not be obtained directly from integrating existing IoT and AI serving platforms by considering the AIoT service reproduction and evolution. In this work, we propose an AIoT platform that empowers developers to build sophisticated and scalable applications. Our platform is derived based on exchangebased RabbitMQ broker and Advanced Message Queuing Protocol (AMQP) to facilitate the communications among heterogeneous data sources and AI models. By incorporating an AMQP broker, it supports diverse data exchanges, AI models chaining, and exible message routing and processing. AI models can be deployed e ciently through containerization with exible and shared data paths to facilitate computations. Hence, developers can focus on service and application requirements. We also present a case study in smart healthcare to validate our design. CCS CONCEPTS• Software and its engineering → Software creation and management; Software system structures; • Networks → Network services.

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