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VID-WIN: Fast video event matching with query-aware windowing at the edge for the internet of multimedia things
(Institute of Electrical and Electronics Engineers (IEEE), 2021-04-23)
Efficient video processing is a critical component in many IoMT applications to detect events of interest. Presently, many window optimization techniques have been proposed in event processing with an underlying assumption ...
Biological applications of knowledge graph embedding models
(Oxford University Press (OUP), 2020-02-17)
Complex biological systems are traditionally modelled as graphs of interconnected biological entities. These graphs, i.e. biological knowledge graphs, are then processed using graph exploratory approaches to perform different ...
Synergy between embedding and protein functional association networks for drug label prediction using harmonic function
(ACM and IEEE, 2020-10-16)
Semi-Supervised Learning (SSL) is an approach to machine learning that makes use of unlabeled data for training with a small amount of labeled data. In the context of molecular biology and pharmacology, one can take advantage ...
Knowledge graph driven approach to represent video streams for spatiotemporal event pattern matching in complex event processing
(World Scientific Publishing, 2020)
Complex Event Processing (CEP) is an event processing paradigm to perform real-time analytics over streaming data and match high-level event patterns. Presently, CEP is limited to process structured data stream. Video ...
Query-driven video event processing for the internet of multimedia things
(VLDB Endowment, 2021-08)
Advances in Deep Neural Network (DNN) techniques have revolutionized video analytics and unlocked the potential for querying
and mining video event patterns. This paper details GNOSIS, an
event processing platform to ...
Toward distributed, global, deep learning using IoT devices
(Institute of Electrical and Electronics Engineers (IEEE), 2021-07-20)
Deep learning (DL) using large scale, high-quality IoT datasets can be computationally expensive. Utilizing such datasets to produce a problem-solving model within a reasonable time frame requires a scalable distributed ...