3.9 Feature optimization using AutoEncoder To enhance the quality and utility of features extracted from DenseNet and SuperPoint, a feature optimization stage is employed using a deep AutoEncoder ...

Key Points MARA Holdings' recent $850 million private offering of convertible notes has caused investor concern about potential stock dilution, leading to a decline in its share price.The company ...

Northern California forecast: Another cool, pleasant day A few clouds and Delta breezes are present this morning and while afternoon temperatures will be warmer than Tuesday, they will still be ...

Deep-learning (DL)-based channel state information (CSI) feedback has attracted a great deal of attention due to its effectiveness in compressing CSI in massive multiple-input multiple-output systems.

Some artists are paying their “respects” to the abandoned grain silos that for decades stood as icons of Midwest decay and as inspiration for urban explorers.

For one of Texas's oldest brick homes, Michael Hsu Office of Architecture both restores elements and slots a new addition.

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We investigate the impact of noise on time-reversal imaging and propose an approach that significantly enhances the detection of objects in noisy environments. Our method involves the decomposition of ...

This repository contains code to train and validate a convolutional VAE with multiple dimensions. - Pull requests · fredlsousa/conv-variational-autoencoder-iron-ore ...

This op comes up in mamba layers and several other places that use 1D depthwise convolutions. Right now it's almost 2x faster to do the blown up multiply followed by a sum, I believe our current ...