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Found 6 papers, 4 papers with code
Human Motion Detection Using Sharpened Dimensionality Reduction and Clustering
SDR has been applied to various real-world datasets, such as human activity sensory data and astronomical datasets.
Visual Cluster Separation Using High-Dimensional Sharpened Dimensionality Reduction
The sharpening step aids this method to preserve cluster separation in the resulting 2D projection.
Aerial Map-Based Navigation Using Semantic Segmentation and Pattern Matching
This paper proposes a novel approach to map-based navigation system for unmanned aircraft.
Scalable Learning With a Structural Recurrent Neural Network for Short-Term Traffic Prediction
With the real traffic speed data measured in the city of Santander, we demonstrate the proposed SRNN outperforms the image-based approaches using the capsule network (CapsNet) by 14. 1% and the convolutional neural network (CNN) by 5. 87%, respectively, in terms of root mean squared error (RMSE).
Structural Recurrent Neural Network for Traffic Speed Prediction
We use a graph of a vehicular road network with recurrent neural networks (RNNs) to infer the interaction between adjacent road segments as well as the temporal dynamics.
A Capsule Network for Traffic Speed Prediction in Complex Road Networks
Traffic flow data from induction loop sensors are essentially a time series, which is also spatially related to traffic in different road segments.
