Results 21 to 30 of about 82,044 (253)

Isolation Forests and Deep Autoencoders for Industrial Screw Tightening Anomaly Detection

Computers, 2022
Within the context of Industry 4.0, quality assessment procedures using data-driven techniques are becoming more critical due to the generation of massive amounts of production data.
Diogo Ribeiro, Luís Miguel Matos, Guilherme Moreira, André Pilastri, Paulo Cortez   +4 more
doaj   +1 more source

Improved Anomaly Detection by Using the Attention-Based Isolation Forest

Algorithms, 2022
A new modification of the isolation forest called the attention-based isolation forest (ABIForest) is proposed for solving the anomaly detection problem.
Lev Utkin, Andrey Ageev, Andrei Konstantinov, Vladimir Muliukha   +3 more
doaj   +1 more source

SI2FM: SID Isolation Double Forest Model for Hyperspectral Anomaly Detection

Remote Sensing, 2023
Hyperspectral image (HSI) anomaly detection (HSI-AD) has become a hot issue in hyperspectral information processing as a method for detecting undesired targets without a priori information against unknown background and target information, which can be ...
Zhenhua Mu, Ming Wang, Yihan Wang, Ruoxi Song, Xianghai Wang   +4 more
doaj   +1 more source

Signature Isolation Forest

CoRR
Functional Isolation Forest (FIF) is a recent state-of-the-art Anomaly Detection (AD) algorithm designed for functional data. It relies on a tree partition procedure where an abnormality score is computed by projecting each curve observation on a drawn dictionary through a linear inner product.
Campi, Marta, Staerman, Guillaume, Peters, Gareth W., Matsui, Tomoko   +3 more
openaire   +4 more sources

Cloud-Empowered Data-Centric Paradigm for Smart Manufacturing

Machines, 2023
In the manufacturing industry, there are claims about a novel system or paradigm to overcome current data interpretation challenges. Anecdotally, these studies have not been completely practical in real-world applications (e.g., data analytics).
Sourabh Dani, Akhlaqur Rahman, Jiong Jin, Ambarish Kulkarni   +3 more
doaj   +1 more source

Condition monitoring method for marine engine room equipment based on machine learning

Zhongguo Jianchuan Yanjiu, 2021
ObjectivesIn order to realize the intelligent condition monitoring of marine engine room equipment, machine learning algorithms are introduced and a condition monitoring method based on manifold learning and an isolation forest is proposed.MethodsAs ...
Ruihan WANG, Hui CHEN, Cong GUAN
doaj   +1 more source

Anomaly detection research using Isolation Forest in Machine Learning

Вестник Дагестанского государственного технического университета: Технические науки
Objective. The study is devoted to assessing the applicability of the Isolation Forest method in the task of detecting anomalies in network traffic data characterized by insufficient markup.
A. S. Kechedzhiev, O. L. Tsvetkova
doaj   +1 more source

A robust soft voting ensemble of the isolation forest model, extended isolation forest model and generalized isolation forest model for multivariate geochemical anomaly recognition

Ore Geology Reviews
Yongliang Chen
exaly   +2 more sources

Online Isolation Forest

CoRR
Accepted at International Conference on Machine Learning (ICML 2024)
Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer, Albert Bifet, Giacomo Boracchi   +4 more
openaire   +3 more sources

Anomaly-based threat detection in smart health using machine learning

BMC Medical Informatics and Decision Making
Background Anomaly detection is crucial in healthcare data due to challenges associated with the integration of smart technologies and healthcare. Anomaly in electronic health record can be associated with an insider trying to access and manipulate the ...
Muntaha Tabassum, Saba Mahmood, Amal Bukhari, Bader Alshemaimri, Ali Daud, Fatima Khalique   +5 more
doaj   +1 more source