Suchergebnisse - real-time anomaly detection algorithms

Anomaly Detection Algorithms for Real-Time Log Data Analysis at Scale

Autoren: András Horváth András Oláh Attila Pintér et al.

Quelle: IEEE Access. 13:136288-136311

Real-time Air Pollution Monitoring in Delhi Using Online Anomaly Detection Algorithms for Streaming Data

Autoren: Santosh Kumar Ray Seba Susan

Quelle: National Academy Science Letters.

Assessing the Complexity and Real-Time Performance of Anomaly Detection Algorithms in Resource-Constrained Environments

Autoren: Romarick Yatagha Oumayma Mejri Karl Waedt et al.

Quelle: 2024 IEEE 20th International Conference on Intelligent Computer Communication and Processing (ICCP). :1-8

Anomaly detection in urban lighting systems using autoencoder and transformer algorithms.

Autoren: Śmiałkowski, Tomasz Czyżewski, Andrzej

Quelle: Scientific Reports; 10/15/2025, Vol. 15 Issue 1, p1-13, 13p

Schlagwörter: AUTOENCODERS, MACHINE learning, ENERGY consumption, OUTLIER detection, MUNICIPAL lighting, ARTIFICIAL intelligence, TRANSFORMER models, REAL-time computing

Novel Real-time In-step Gait Anomaly Detection Algorithms

Autoren: Jakob Rostovski Andrei Krivošei Alar Kuusik et al.

Towards Design Principles for a Real-Time Anomaly Detection Algorithm Benchmark Suited to Industrie 4.0 Streaming Data

Autoren: Stahmann, Philip Rieger, Bodo

Quelle: Proceedings of the Annual Hawaii International Conference on System Sciences.

Schlagwörter: Business Strategies, benchmark, 9. Industry and infrastructure, Data Analytics, real-time anomaly detection algorithms, Control Systems, industrie 4.0, streaming data

Dateibeschreibung: application/pdf

Zugangs-URL: http://scholarspace.manoa.hawaii.edu/bitstream/10125/80106/1/0617.pdf

Network Traffic Anomaly Detection Algorithms on Distributed Systems using Cognitive Intelligence

Autoren: Ning Pan

Quelle: Scalable Computing: Practice and Experience. 26:2286-2295

Real-Time Unsupervised Anomaly Detection in the CMS Level-1 Trigger

Autoren: Glowacki, Maciej Mikolaj

A Benchmark for Real-Time Anomaly Detection Algorithms Applied in Industry 4.0

Autoren: Philip Stahmann Bodo Rieger

Quelle: Lecture Notes in Computer Science ISBN: 9783031255984

Anomaly detection in urban lighting systems using autoencoder and transformer algorithms

Autoren: Tomasz Śmiałkowski Andrzej Czyżewski

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-13 (2025)

Schlagwörter: Anomaly detection, Urban lighting systems, Autoencoder, Transformer, Computational efficiency, Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2045-2322

Zugangs-URL: https://doaj.org/article/8cb473ce1da94667ba39a45be31d39e7

Real-Time Human Action Anomaly Detection Through Two-Stream Spatial-Temporal Networks

Autoren: Chuan Peng Zebin Jiang Mao Lin et al.

Quelle: IEEE Access, Vol 13, Pp 66774-66786 (2025)

Schlagwörter: action recognition, real-world infrastructure, deep learning, Anomaly detection, Electrical engineering. Electronics. Nuclear engineering, human-object interaction, TK1-9971

Zugangs-URL: https://doaj.org/article/a7e77ac7f92d40459df09ece98b15b6d

A Low-Complexity Hyperspectral Anomaly Detection Algorithm and Its FPGA Implementation

Autoren: Jie Lei Geng Yang Weiying Xie et al.

Quelle: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 907-921 (2021)

Schlagwörter: Ocean engineering, morphological reconstruction, high-level synthesis (HLS), QC801-809, hyperspectral image (HSI), real-time implementation, Geophysics. Cosmic physics, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, Anomaly detection, 02 engineering and technology, TC1501-1800, guided filtering

Zugangs-URL: https://ieeexplore.ieee.org/ielx7/4609443/9314330/09240046.pdf
https://doaj.org/article/423a0d54b73a427386b019b6fbb65d00
https://dblp.uni-trier.de/db/journals/staeors/staeors14.html#LeiYXLJ21
https://ieeexplore.ieee.org/document/9240046
http://ieeexplore.ieee.org/document/9240046
https://ui.adsabs.harvard.edu/abs/2021IJSTA..14..907L/abstract

An LSTM Encoder-Decoder Approach for Unsupervised Online Anomaly Detection in Machine Learning Packages for Streaming Data

Autoren: Belacel, Nabil Richard, Rene Xu, Zhicheng Max

Quelle: 2022 IEEE International Conference on Big Data (Big Data). :3348-3357

Schlagwörter: 02 engineering and technology, streaming data, unsupervised learning, online anomaly detection, anomaly detection, scikit-multiflow, machine learning, real-time systems, big data, machine learning algorithms, 0202 electrical engineering, electronic engineering, information engineering, LSTM-AE, recurrent neural networks, computer architecture

Zugangs-URL: https://nrc-publications.canada.ca/eng/view/object/?id=e63aaf88-2da6-4f1a-a971-5a84e3325a87
https://doi.org/10.1109/bigdata55660.2022.10020872

An unsupervised machine learning approach for real-time damage detection in bridges

Autoren: Bayane, Imane Leander, John Karoumi, Raid

Quelle: Engineering structures. 308

Schlagwörter: Bridge, brittle cracking, Damage, Machine learning, Monitoring, Real-time detection, Unsupervised algorithms

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-345759
https://doi.org/10.1016/j.engstruct.2024.117971

Integrating AI Models for Enhanced Real-Time Cybersecurity in Healthcare: A Multimodal Approach to Threat Detection and Response.

Autoren: Ali, Tariq Emad Ali, Faten Imad Eyvazov, Farid et al.

Quelle: Procedia Computer Science. 2025, Vol. 259, p108-119. 12p.

Schlagwörter: Detection algorithms, Public health infrastructure, Anomaly detection (Computer security), Artificial intelligence, Cyberterrorism, Deep learning

Improving Machine Self-Diagnosis with an Instance-Based Selector for Real-Time Anomaly Detection Algorithms

Autoren: Philip Stahmann Jon Oodes Bodo Rieger

Quelle: Lecture Notes in Business Information Processing ISBN: 9783031065293

Tackling the anomaly detection challenge in large-scale wireless sensor networks.

Autoren: Zhukabayeva, Tamara Adamova, Aigul Zholshiyeva, Lyazzat et al.

Quelle: International Journal of Electrical & Computer Engineering (2088-8708); Apr2025, Vol. 15 Issue 2, p2479-2490, 12p

Schlagwörter: WIRELESS sensor network security, ANOMALY detection (Computer security), DETECTION algorithms, K-nearest neighbor classification, MACHINE learning

REAL TIME AIR QUALITY PREDICTION AND ANOMALY DETECTION

Autoren: Dr.S.Ariffa Begum

Quelle: INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT. :1-5

Schlagwörter: 13. Climate action, 11. Sustainability, 3. Good health

Robust anomaly detection algorithms for real-time big data: Comparison of algorithms

Autoren: Zirije Hasani

Quelle: 2017 6th Mediterranean Conference on Embedded Computing (MECO). :1-6

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy

Zugangs-URL: http://ieeexplore.ieee.org/document/7977130/
https://ieeexplore.ieee.org/document/7977130/
https://dblp.uni-trier.de/db/conf/meco/meco2017.html#Hasani17

Centralized VoIP Monitoring Architecture: A Scalable Framework for Real-Time Quality Assurance and Proactive Fault Management in Distributed Telecommunications Networks.

Autoren: Munnaluru, Pardhiva Janardhana Krishna

Quelle: Journal of Computer Science & Technology Studies; 2025, Vol. 7 Issue 6, p952-958, 13p

Schlagwörter: TELECOMMUNICATION network management, COMMUNICATION infrastructure, DETECTION algorithms, FAULT tolerance (Engineering), ANOMALY detection (Computer security), INTERNET telephony