Neural networks are algorithmic systems created based on the principle of the human nervous system. They consist of many ...

Abstract: In this article, a framework for the analog implementation of a deep convolutional neural network (CNN) is introduced and used to derive a new circuit architecture which is composed of an ...

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ...

Researchers in Turkey have developed BCECNN, an AI model that detects breast cancer with 98.75% accuracy and explains its reasoning through visual heatmaps, improving doctor trust in AI diagnostics.

Abstract: Early detection of skin cancer (SC) is paramount for effective treatment. Although convolutional neural networks (CNN) have facilitated automated learning of high-level features from ...

Pea-sized brains grown in a lab have for the first time revealed the unique way neurons might misfire due to schizophrenia and bipolar disorder, psychiatric ailments that affect millions of people ...

Bridges matter because they unlock the true potential of blockchains by letting assets and data move freely between disconnected networks. They let you use Ethereum’s smart apps with Bitcoin’s ...

Deep learning-based image steganalysis has progressed in recent times, with efforts more concerted toward prioritizing detection accuracy over lightweight frameworks. In the context of AI-driven ...

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...