TinyML is an incredibly powerful piece of software, and you can easily train your own model and deploy it on an ESP32.

This project applies deep learning to detect anomalies in network traffic data using autoencoders. By learning normal traffic patterns, the model can identify irregular activity that may indicate ...

This mobile application uses behavioral and sensor data from a user's interactions to detect potential anomalies like stress, fatigue, or erratic behavior patterns using a trained LSTM Autoencoder ...

Abstract: Image reconstruction-based methods with autoencoder have been widely used for unsupervised anomaly detection. By training the reconstruction on normal ...

Abstract: Inspired by the complexity and diversity of biological neurons, a quadratic neuron is proposed to replace the inner product in the current neuron with a simplified quadratic function.