Výsledky vyhledávání - "Optimized deep autoencoder"

GOOSE-Optimized Deep Autoencoder for Intrusion Detection in IoMT Networks: A Scalable and Efficient Approach for Healthcare Security

Autoři: Pooja Puspita Priyadarshani Janmenjoy Nayak Pandit Byomakesha Dash

Zdroj: Arabian Journal for Science and Engineering.

Optimized deep autoencoder and BiLSTM for intrusion detection in IoTs-Fog computing

Autoři: Abdullah Alqahtani

Zdroj: Multimedia Tools and Applications. 84:4907-4943

Optimized Deep Autoencoder Model for Internet of Things Intruder Detection

Autoři: Badr Lahasan Hussein Samma

Zdroj: IEEE Access, Vol 10, Pp 8434-8448 (2022)

Témata: IoT, Artificial intelligence, IoT Security, Computer Networks and Communications, QA75 Electronic computers. Computer science, Anomaly detection, 02 engineering and technology, Pattern recognition (psychology), Anomaly Detection in High-Dimensional Data, Characterization and Detection of Android Malware, Deep Learning, Artificial Intelligence, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, autoencoder, Particle swarm optimization, Intrusion detection system, Deep learning, Autoencoder, Computer science, anomaly detection, TK1-9971, Intrusion Detection, Detection, Computer Science, Physical Sciences, Signal Processing, Network Intrusion Detection and Defense Mechanisms, Electrical engineering. Electronics. Nuclear engineering, Botnet Detection, Classifier (UML), k-nearest neighbors algorithm

Popis souboru: application/pdf

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/9668973/09684419.pdf
https://doaj.org/article/cf4d4df56d8f4b04985bbda98a9dc86b

OPTIMIZED DEEP AUTOENCODER WITH L1 REGULARIZATION AND DROPOUT FOR ANOMALY DETECTION IN 6G NETWORK SLICING

Autoři: Jennifer Kaunang, Valencia Claudia Alamsyah, Nur Parama Yoga, Titan a další

Zdroj: Jurnal Techno Nusa Mandiri; Vol. 22 No. 2 (2025): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of September 2025; 189-194 ; 2527-676X ; 1978-2136 ; 10.33480/techno.v20i2

Témata: 6g network slicing, anomaly detection, autoencoder, dropout, regularization

Popis souboru: application/pdf

Relation: https://ejournal.nusamandiri.ac.id/index.php/techno/article/view/6912/1520; https://ejournal.nusamandiri.ac.id/index.php/techno/article/view/6912

Dostupnost: https://ejournal.nusamandiri.ac.id/index.php/techno/article/view/6912

Action recognition using optimized deep autoencoder and CNN for surveillance data streams of non-stationary environments

Autoři: Amin Ullah Khan Muhammad Ijaz Ul Haq a další

Zdroj: Future Generation Computer Systems. 96:386-397

Témata: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://dblp.uni-trier.de/db/journals/fgcs/fgcs96.html#UllahMHB19
https://doi.org/10.1016/j.future.2019.01.029
https://www.sciencedirect.com/science/article/pii/S0167739X18318533

Optimized deep autoencoder and BiLSTM for intrusion detection in IoTs-Fog computing.

Autoři: Alqahtani, Abdullah

Zdroj: Multimedia Tools & Applications; Mar2025, Vol. 84 Issue 8, p4907-4943, 37p

Témata: LONG short-term memory, OPTIMIZATION algorithms, ARTIFICIAL intelligence, AUTOENCODERS, TELECOMMUNICATION

Efficient Online Big Data Stream Clustering Using Dual Interactive Wasserstein Generative Adversarial Network.

Autoři: Matheswaran, Suresh Nachimuthu, Nandhagopal Prakash, G.

Zdroj: International Journal on Artificial Intelligence Tools; Aug2024, Vol. 33 Issue 5, p1-24, 24p

Témata: GENERATIVE adversarial networks, OPTIMIZATION algorithms, REAL-time computing, STREAMING video & television, CENTROID, DEEP learning

基于O-DAE和SVDD的汽轮机异常检测方法. (Chinese)

Alternate Title: A steam turbine anomaly detection method based on O-DAE and SVDD. (English)

Autoři: 许伟明 李学敏 张 祎 a další

Zdroj: Zhejiang Electric Power; 7/25/2023, Vol. 42 Issue 7, p102-109, 8p

A transfer learning-based efficient spatiotemporal human action recognition framework for long and overlapping action classes.

Autoři: Bilal, Muhammad Maqsood, Muazzam Yasmin, Sadaf a další

Zdroj: Journal of Supercomputing; Feb2022, Vol. 78 Issue 2, p2873-2908, 36p

Témata: HUMAN behavior, DEEP learning, CLASS actions, BEHAVIORAL assessment, VIDEO surveillance, COMPUTER vision

HARNet: an enhanced deep learning-based human activity recognition model.

Autoři: Talukder, Md. Alamin Kazi, Mohsin Uddin, Md. Ashraf

Zdroj: Cluster Computing; 2025, Vol. 28 Issue 11, p1-19, 19p

Témata: HUMAN activity recognition, DEEP learning, CONVOLUTIONAL neural networks, LONG short-term memory, VIDEO processing

Deep learning for intrusion detection in emerging technologies: a comprehensive survey and new perspectives.

Autoři: Neto, Euclides Carlos Pinto Iqbal, Shahrear Buffett, Scott a další

Zdroj: Artificial Intelligence Review; Nov2025, Vol. 58 Issue 11, p1-63, 63p

Témata: DEEP learning, INTRUSION detection systems (Computer security), EDGE computing, INTERNET security, TECHNOLOGICAL innovations, INTERNET of things, CLOUD computing

Fog-empowered anomaly detection in IoT networks using one-class asymmetric stacked autoencoder.

Autoři: Ayad, Aya G. Sakr, Nehal A. Hikal, Noha A.

Zdroj: Cluster Computing; 2025, Vol. 28 Issue 8, p1-28, 28p

Témata: ANOMALY detection (Computer security), INTERNET of things, REAL-time computing, DEEP learning, FEATURE extraction, HOME security measures, EDGE computing

Advanced deep learning approach for the fault severity classification of rolling-element bearings.

Autoři: Parmar, Vivek Layek, Shirshendu Bhushan, Megha a další

Zdroj: Scientific Reports; 10/2/2025, Vol. 15 Issue 1, p1-20, 20p

Témata: DEEP learning, FAULT diagnosis, SIGNAL processing, PARTICLE swarm optimization, MECHANICAL vibration research, ROLLER bearings, CONVOLUTIONAL neural networks, ARTIFICIAL neural networks

Lightweight intrusion detection system for IoT with improved feature engineering and advanced dynamic quantization.

Autoři: Misrak, Semachew Fasika Melaku, Henock Mulugeta

Zdroj: Discover Internet of Things; 9/24/2025, Vol. 5 Issue 1, p1-34, 34p

Témata: INTERNET of things, DEEP learning, SIGNAL quantization, OPTIMIZATION algorithms, INTERNET security, FEATURE selection, INTRUSION detection systems (Computer security)

A Vision-Based AI framework for skill transfer and robotic replication of Miao embroidery techniques.

Autoři: Chen, Ling Chen, Jing Su, Zhi a další

Zdroj: Signal, Image & Video Processing; Sep2025, Vol. 19 Issue 9, p1-13, 13p

A Comprehensive Methodological Survey of Human Activity Recognition Across Diverse Data Modalities.

Autoři: Shin, Jungpil Hassan, Najmul Miah, Abu Saleh Musa a další

Zdroj: Sensors (14248220); Jul2025, Vol. 25 Issue 13, p4028, 73p

Témata: HUMAN activity recognition, MACHINE learning, QUANTITATIVE research, DEEP learning

A lightweight IoT intrusion detection method based on two-stage feature selection and Bayesian optimization.

Autoři: Zhang, Dainan Huang, Dehui Chen, Yanying a další

Zdroj: AIMS Electronics & Electrical Engineering; 2025, Vol. 9 Issue 3, p1-31, 31p

Témata: INTERNET of things, INTRUSION detection systems (Computer security), FEATURE selection, MATHEMATICAL optimization, BOOSTING algorithms

Optimizing machine learning algorithms for fault classification in rolling bearings: A Bayesian Optimization approach.

Autoři: Yousaf, Muhammad Zain Guerrero, Josep M. Sadiq, Muhammad Tariq

Zdroj: Engineering Applications of Artificial Intelligence. Jun2025, Vol. 150, pN.PAG-N.PAG. 1p.

Témata: *MACHINE learning, *LONG short-term memory, *AUTOENCODERS, *CENTRAL processing units, *ROLLER bearings, *DEEP learning

A machine learning based authentication and intrusion detection scheme for IoT users anonymity preservation in fog environment.

Autoři: Oliullah, Khondokar Whaiduzzaman, Md Mahi, Md. Julkar Nayeen a další

Zdroj: PLoS ONE; 6/16/2025, Vol. 20 Issue 6, p1-32, 32p

Témata: ENSEMBLE learning, ELLIPTIC curve cryptography, DETECTION algorithms, SYMMETRIC functions, ANOMALY detection (Computer security), INTRUSION detection systems (Computer security), COMPUTER passwords

Forecasting Data-Driven Performance: Learning-based Data Manipulation Detection System.

Autoři: Cheng-Shian Lin Sin-Man Wong Chien-Chang Chen

Zdroj: International Journal of Performance Measurement; Jun2025, Vol. 15 Issue 1, p58-78, 21p

Témata: LONG short-term memory, AUTOENCODERS, TIME series analysis, RELIABILITY in engineering, ANOMY