Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera images ...
College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang, China The final, formatted version of the article will be published soon. This study proposes a ...
ABSTRACT: This work presents an innovative Intrusion Detection System (IDS) for Edge-IoT environments, based on an unsupervised architecture combining LSTM networks and Autoencoders. Deployed on ...
Abstract: Video anomaly detection (VAD) is of great importance for a variety of real-time applications in video surveillance. Most deep learning-based anomaly detection algorithms adopt a one-class ...
The ability to detect single photons (the smallest energy packets constituting electromagnetic radiation) in the infrared range has become a pressing need across numerous fields, from medical imaging ...
A complete workflow for building, training, and deploying a lightweight LSTM Autoencoder anomaly detector for temperature data on the ESP32 microcontroller—without TensorFlow or TFLite. This project ...
We support Python 3.11+ and PyTorch 2.4.0+. Please install the correct PyTorch version according to your own hardware settings. We provide the HDF5 files and ...
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