Abstract: Machine learning and artificial intelligence (AI) have already penetrated so deeply into our life and work that you might have forgotten what interactions with machines used to be like. We ...

ABSTRACT: The rapid growth of unlabeled time-series data in domains such as wireless communications, radar, biomedical engineering, and the Internet of Things (IoT) has driven advancements in ...

This repository contains numerous applications of autoencoder neural networks. Projects include image denoising, detection of infected cells, and processing of the MNIST dataset. Each application ...

UCF's 'bridge doctor' combines imaging, neural network to efficiently evaluate concrete bridges' safety Date: May 16, 2025 Source: University of Central Florida Summary: New research details how ...

Blockchain networks often exhibit lower throughput rates compared to centralized payment systems due to the intricate node verification process during data propagation. Improving blockchain ...

We use this handy neural mechanism to learn ... the traditional Hopfield network model is powerful, but it doesn't tell the full story of how new information guides memory retrieval.

Department of Computer Science, Vanderbilt University, 2201 West End Ave, Nashville, Tennessee 37235, United States ...

Five different convolutional neural networks (CNNs)-FCN, LR-ASPP ... It ensures that each feature layer in every Dense block is fully connected, allowing the input of each feature layer to be linked ...