First, to reduce the distance between multi-source homogeneous signals in the feature space, we design a novel Contrastive Pairs AutoEncoder (CPAE), which is for feature alignment before aggregating ...

WASHINGTON — Lockheed Martin is launching a new initiative called “AI Fight Club,” a virtual battleground where companies can test their artificial intelligence algorithms for use in ...

It uses an LSTM (Long Short-Term Memory) autoencoder model built with TensorFlow/Keras to learn normal patterns from your metrics and identify deviations. The system includes scripts for data ...

PCA + MiniBatch KMeans offers a strong trade-off between performance and computational cost. SAE + DBSCAN produces high-quality clusters but requires significantly more training time. Visual ...

At the same time, quantum computing is poised to disrupt cryptography. In particular, Shor’s algorithm, a quantum algorithm developed in 1994, can efficiently factor large numbers and compute discrete ...

In this paper, we propose a cell scene division and visualization method based on autoencoder and K-means algorithm. We train an autoencoder network to conduct the dimension reduction of the wireless ...