Discovering spatio-temporal dependencies based on time-lag in intelligent transportation data
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DOI: 10.1016/j.neucom.2016.06.084
Abstract: Abstract Learning spatio-temporal dependency structure is meaningful to characterize causal or statistical relationships. In many real-world applications, dependency structure is often characterized by time-lag between variables. For example, traffic system and climate, time lag is… read more here.
Keywords: spatio temporal; temporal dependencies; time; time lag ... See more keywords
Multi-Scale and Single-Scale Fully Convolutional Networks for Sound Event Detection
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DOI: 10.1016/j.neucom.2020.09.038
Abstract: Abstract Among various Sound Event Detection (SED) systems, Recurrent Neural Networks (RNN), such as long short-term memory unit and gated recurrent unit, is used to capture temporal dependencies, but it is confined in its length… read more here.
Keywords: detection; convolutional networks; temporal dependencies; fully convolutional ... See more keywords
TCGL: Temporal Contrastive Graph for Self-Supervised Video Representation Learning
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DOI: 10.1109/tip.2022.3147032
Abstract: Video self-supervised learning is a challenging task, which requires significant expressive power from the model to leverage rich spatial-temporal knowledge and generate effective supervisory signals from large amounts of unlabeled videos. However, existing methods fail… read more here.
Keywords: self supervised; representation; unlabeled videos; temporal contrastive ... See more keywords
ESTNet: Embedded Spatial-Temporal Network for Modeling Traffic Flow Dynamics
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2022.3167019
Abstract: Accurate spatial-temporal prediction is a fundamental building block of many real-world applications such as traffic scheduling and management, environment policy making, and public safety. This problem is still challenging due to nonlinear, complicated, and dynamic… read more here.
Keywords: network; temporal dependencies; embedded spatial; traffic ... See more keywords