As we venture further into space, the need for Artificial Intelligence (AI) based anomaly detection algorithms for space operations significantly escalates. These algorithms are essential for ...

In the POCS-based clustering algorithm, ... To this end, an off-the-shelf FaceNet model and an autoencoder network are adopted to synthesize two sets of feature embeddings from the Five Celebrity ...

To overcome these limitations, we introduce the concept of a local conformal autoencoder (LOCA), which is a deep learning-based algorithm, specifically suited to burst measurements. LOCA is realized ...

This project contains an Autoencoder, built and trained using Tensorflow, and used to vectorize images, so a kNN algorithm can check for image similarity. It contains two major Python notebooks, one ...

In this paper, we propose a new algorithm called N2A-SVM (Node2vec Autoencoder-Support Vector Machine) to predict genes associated with Parkinson's disease. The contributions of our work are as ...

A C# implementations of the algorithm DTAE [1] for categorical data. An example of using this implementation In the file Program.cs, specify the paths to the training (1tra.csv) and testing (1tst.csv) ...