Machine learning is an integral part of high-stakes decision-making in a broad swath of human-computer interactions. You ...

Two supervised machine learning methods, among them Support Vector Machine (SVM) and Artificial Neural Networks (ANN), are employed in Network Intrusion Detection to identify whether the data ...

Eighteen years, multiple countries, and countless disappointments—that is the back‑story of a couple who, at last, are expecting their first child. Their turning‑point came not from another round of ...

This review covers recent advances in artificial intelligence (AI) for aquatic species identification and conservation, ...

At its core, algorithmic journalism uses data analysis and machine learning tools to automate parts of news production. These ...

Specially, as a deep learning based solution for detecting the MRCE signals in the uplink massive MIMO systems, the convolutional-neural-network aided nonlinear detection (CAD) algorithms are proposed ...

An experimental study shows that already small-scale quantum computers can boost the performance of machine learning algorithms.

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

The study shows that machine learning and deep learning algorithms can accurately classify tree species using individual tree point clouds, and the operation process of PointMLP is more concise and ...

The idea proposes a machine learning program for the detection and classification of defects in PCBs using a YOLOv5 object detection algorithm and an Inception v3 CNNbased approach.

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes ...