Autoencoder: A specialised neural network that learns an efficient, compressed representation of input data by training to reproduce the original signal after dimensionality reduction.

Nowadays, the rapid growth of data stream from different sources has needed the development of effective Anomaly Detection (AD) methods. The existing unsupervised Deep Learning (DL) approaches learnt ...

We apply a spectral masking autoencoder in an asymmetric structure to extract superior prior features from training data and regularize the network. Experimental results on remote sensing HSI datasets ...

Aimed at AI/ML applications, Renesas’ RA8P1 MCUs leverage an Arm Ethos-U55 neural processing unit (NPU) delivering 256 GOPS ...

Several district heating networks planned for the UK are looking to utilize waste heat generated by data centers. The UK’s Department for Energy Security and Net Zero (DESNZ) has published a list of ...

Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like ...

Researchers have developed a self-tuning AI framework that dynamically filters noisy graph data to boost reliability and accuracy across industries ...

A new technical paper titled “Hardware-software co-exploration with racetrack memory based in-memory computing for CNN inference in embedded systems” was published by researchers at National ...

Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the ...

Using a neural network trained with simulations of supermassive black holes, astronomers have found that the one at the center of the Milky Way, Sagittarius A*, likely rotates at maximum speed.

In a new independent research report by SuperMicrobiologistes, technicians and lab managers share their work experiences using the Inlabtec Serial Diluter. To help microbiology labs solve ...