Scientific Research Publishing

Covariant-Scale: Riemannian Manifold Learning for Scale-Invariant Video Anomaly Detection ()

Video-Based Anomaly Detection, Urban Surveillance, Scale-Projective Ambiguity, Riemannian Manifold, Scale-Covariant Tracking, ...
pv magazine International

Domain adaptation framework for PV power forecasting

A team of researchers have developed a domain adaption framework capable of transferring knowledge from solar power plants with abundant data to plants that need to be trained without labelled data.
GitHub

Dynamical Dual Latent Space Variational Autoencoder Model with Koopman Constraint for Semi-Supervised Soft Sensor Application

├── data_pre/ # Data preprocessing modules │ ├── data_pre.py # Data preprocessing script │ └── dataset.py # Dataset class definition ├── dataset/ # Data directory │ ├── SRU_data.npy # Process data in ...
Automation World

Inductive Angle Encoders

Flux has released a new 300mm size option for its Ind-Max range of inductive angle encoders for harsh environments. These encoders use inductive technology to deliver non-contact, wear-free ...
Scientific Research Publishing

An Enhanced and Explainable Hybrid Ensemble Intrusion Detection System for Connected Vehicles ()

1 Department of Computer Science and Engineering, Oakland University, Rochester, MI, USA. 2 Department of Computer Science, Kettering University, Flint, MI, USA. Intelligent vehicles require strong ...
marktechpost

How Latent Vector Fields Reveal the Inner Workings of Neural Autoencoders

Neural networks are designed to learn compressed representations of high-dimensional data, and autoencoders (AEs) are a widely-used example of such models. These systems employ an encoder-decoder ...
IEEE

Variational Autoencoder-Based Vehicle Trajectory Prediction with an Interpretable Latent Space

Abstract: This paper introduces the Descriptive Variational Autoencoder (DVAE), an unsupervised and end-to-end trainable neural network for predicting vehicle trajectories that provides partial ...