Results 171 to 180 of about 414,528 (301)

Unsupervised Learning of Mixture Models with a Uniform Background Component. [PDF]

, 2018
Sida Liu, Adrian Barbu
openalex  

Neural Predictive Coding Using Convolutional Neural Networks Toward Unsupervised Learning of Speaker Characteristics [PDF]

, 2019
Arindam Jati, Panayiotis Georgiou
openalex   +1 more source

Deep Reinforcement Learning Approaches for Sensor Data Collection by a Swarm of UAVs

Advanced Intelligent Systems, EarlyView.
This article presents four decentralized reinforcement learning algorithms for autonomous data harvesting and investigates how collaboration improves collection efficiency. It also presents strategies to minimize training times by improving model flexibility, enabling algorithms to operate with varying number of agents and sensors.
Thiago de Souza Lamenza, Bruno José Olivieri de Souza, Markus Endler   +2 more
wiley   +1 more source

Single-station analysis of Campi Flegrei (Italy) seismic signals using multiscale entropy and unsupervised learning. [PDF]

Sci Rep
Grimaldi A, Amoroso O, Scarpetta S, Convertito V, Napolitano F, Messuti G, Capuano P, Nardone L, Gaudiosi G, Galluzzo D.   +9 more
europepmc   +1 more source

ANALISA AKURASI PERMODELAN SUPERVISED DAN UNSUPERVISED LEARNING MENGGUNAKAN DATA MINING

, 2019
Warnia Nengsih
openalex   +2 more sources

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

PROTECT: Protein circadian time prediction using unsupervised learning. [PDF]

iScience
Ansary Ogholbake A, Cheng Q.
europepmc   +1 more source

An Intelligent Feature Engineering‐Driven Hybrid Framework for Adversarial Domain Name System Tunneling Detection

Advanced Intelligent Systems, EarlyView.
This study presents a novel framework that enhances the reliability of DNS traffic monitoring using a hybrid long short‐term memory‐deep neural network (LSMT‐DNN) architecture, enabling robust detection of adversarial DNS tunneling. The proposed framework leverages feature extraction from DNS traffic patterns, including domain request sequences, query ...
Ahmad Almadhor, Shtwai Alsubai, Monji Mohamed Zaidi, Natalia Kryvinska, Abdullah Al Hejaili, Sidra Abbas   +5 more
wiley   +1 more source

An Unsupervised Learning Algorithm for the Automatic Classification of Coronary Artery Lesions. [PDF]

Cureus
Szopinska J, Regulski PA, Mazurek M, Grabowski M, Wendykier P, Jozwiak R.   +5 more
europepmc   +1 more source

Supervised and Unsupervised Learning Using Scikit Learn for Predictive Analytics [PDF]

B Angalaparameswari, P Murugeswari, Kamalkumar T   +2 more
openalex   +1 more source