Abstract: Efficient compression of sparse point cloud geometry remains a critical challenge in 3D content processing, particularly for low-rate scenarios where conventional codecs struggle to maintain ...

AutoencoderZ is an advanced Autoencoder model designed for dimensionality reduction of various data types, such as seismometer and strainmeter data. It features an encoder-decoder architecture that ...

This project shows how to find anomalies in financial time series data, specifically the stock values of Apple (AAPL), using a LSTM Autoencoder. Stock price anomalies may be a sign of major market ...

Abstract: This paper introduces an Asymmetric Autoencoder (AAE)-driven data compression framework for efficient management of energy, bandwidth, and transmitter complexity in a Wireless Sensor Network ...