Deep temporal state perception towards artificial cyber-physical systems
Cyber–physical systems (CPS), as the cornerstone of smart city, has been attracting great
interest from academia and industry. It aims to monitor/control physical components via …
interest from academia and industry. It aims to monitor/control physical components via …
An event-based categorization model using spatio-temporal features in a spiking neural network
This paper introduces an event-based categorization model to explore neuromorphic
computing for object recognition. The proposed method makes full use of the precise timing …
computing for object recognition. The proposed method makes full use of the precise timing …
Deep-learning-based multivariate time-series classification for indoor/outdoor detection
Recently, the topic of indoor outdoor detection (IOD) has seen its popularity increase, as IOD
models can be leveraged to augment the performance of numerous Internet of Things and …
models can be leveraged to augment the performance of numerous Internet of Things and …
End-to-end multi-modal behavioral context recognition in a real-life setting
Smart devices of everyday use (such as smartphones and wearables) are increasingly
integrated with sensors that provide immense amounts of information about a person's daily …
integrated with sensors that provide immense amounts of information about a person's daily …
Context-aware deep representation learning for geo-spatiotemporal analysis
The emergence of remote sensing technologies coupled with local monitoring workstations
enables us the unprecedented ability to monitor the environment in large scale. Information …
enables us the unprecedented ability to monitor the environment in large scale. Information …
Deep-Learning-Based Scenario Recognition With GNSS Measurements on Smartphones
Z Dai, C Zhai, F Li, W Chen, X Zhu… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
Smartphones are in everyone's hands for applications including navigation-and localization-
based services, and scenario recognition is critical for seamless indoor and outdoor …
based services, and scenario recognition is critical for seamless indoor and outdoor …
Qualitydeepsense: Quality-aware deep learning framework for internet of things applications with sensor-temporal attention
Deep neural networks are becoming increasingly popular in mobile sensing and computing
applications. Their capability of fusing multiple sensor inputs and extracting temporal …
applications. Their capability of fusing multiple sensor inputs and extracting temporal …
Time series classification via enhanced temporal representation learning
K Wang, C Wang, Y Wang, W Luo… - 2021 IEEE 6th …, 2021 - ieeexplore.ieee.org
Due to the booming of time series (a temporal data sequence, including continuous
recorded values and timestamps), time series classification has been considered as one of …
recorded values and timestamps), time series classification has been considered as one of …
[PDF][PDF] ST-EVNet: Hierarchical spatial and temporal feature learning on space-time event clouds
Recent approaches for video-based gesture recognition rely on extracting different types of
features, hand-focus attention and combination of them to achieve good performance. These …
features, hand-focus attention and combination of them to achieve good performance. These …
MVF-Net: A multi-view fusion network for event-based object classification
Event-based object recognition has drawn increasing attention for event cameras'
distinguished advantages of low power consumption and high dynamic range. For this new …
distinguished advantages of low power consumption and high dynamic range. For this new …