This project explores segmentation and reconstruction of noisy synthetic particles (circles with triangle distractors) using a convolutional autoencoder (VAE-style latent representation). It includes ...

This project provides an unsupervised learning solution for detecting anomalies in time-series data, specifically demonstrated on synthetic network traffic. It leverages a Long Short-Term Memory (LSTM ...

Abstract: Feature extraction is an essential step in traditional machine learning approaches for detecting upper limb use employing movement data from inertial measurement units. However, manual ...

Abstract: In this paper we present a new implementation of a Variational Autoencoder (VAE) for the calibration of sensors. We propose that the VAE can be used to calibrate sensor data by training the ...

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Written in Rust, the PyApp utility wraps up Python programs into self-contained click-to-run executables. It might be the easiest Python packager yet. Every developer knows how hard it is to ...