Výsledky vyhledávání - conventional neural network-autoencoder (architektur* OR architecture*)

Detecting network intrusions in cyber-physical systems using deep autoencoder-based dimensionality reduction approach and deep neural networks.

Autoři: Ibor, A. E. Egete, D. O. Otiko, A. O. a další

Zdroj: Journal of Nigerian Society of Physical Sciences; Aug2025, Vol. 7 Issue 3, p1-15, 15p

Témata: ARTIFICIAL neural networks, FEEDFORWARD neural networks, AUTOENCODERS, CYBER physical systems, COMPUTER network traffic, DEEP learning

Deep learning in microbiome analysis: a comprehensive review of neural network models.

Autoři: Przymus, Piotr Rykaczewski, Krzysztof Martín-Segura, Adrián a další

Zdroj: Frontiers in Microbiology; 2025, p1-27, 27p

Témata: MACHINE learning, ARTIFICIAL neural networks, NATURAL language processing, PATTERN recognition systems, DEEP learning, FEATURE extraction

A systematic literature review on advances in brain tumor detection using deep learning and explainable AI methods.

Autoři: Tehsin, Sara Nasir, Inzamam Mashood Damaševičius, Robertas

Zdroj: Network Modeling & Analysis in Health Informatics & Bioinformatics; 11/20/2025, Vol. 14 Issue 1, p1-23, 23p

Detecting antibiotic resistance: classical, molecular, advanced bioengineering, and AI-enhanced approaches.

Autoři: Aldea, Alexandru Constantin Diguṭă, Filofteia Camelia Presacan, Oriana a další

Zdroj: Frontiers in Microbiology; 2025, p1-33, 33p

Témata: DRUG resistance in bacteria, ARTIFICIAL intelligence, BIOENGINEERING, DETECTION algorithms, MICROFLUIDICS, CRISPRS, BIOSENSORS, MOLECULAR diagnosis

An Effective Approach for Wearable Sensor-Based Human Activity Recognition in Elderly Monitoring.

Autoři: Errafik, Youssef Dhassi, Younes Baghrous, Mohamed a další

Zdroj: BioMedInformatics; Sep2025, Vol. 5 Issue 3, p38, 21p

High-Fidelity Emotion Recognition via SDR-Based Wireless Sensing and Deep Learning.

Autoři: Ullah, Hikmat AbuAli, Najah Ullah, Farman a další

Zdroj: Cognitive Computation; Dec2025, Vol. 17 Issue 6, p1-18, 18p

The Convergence of Polymer Science and Predictive Modeling for Noninvasive Glucose Monitoring.

Autoři: Lee, Ju-Hwan Yun, Hong-Sik Jeon, Hee-Jae

Zdroj: Pharmaceutics; Nov2025, Vol. 17 Issue 11, p1488, 18p

Témata: BLOOD sugar monitoring, ARTIFICIAL intelligence, HYDROGELS, POLYMERS, BIOSENSORS, IMPRINTED polymers, PREDICTION models, GLYCEMIC control

Universal semantic feature extraction from EEG signals: a task-independent framework.

Autoři: Ahmadi, Hossein Mesin, Luca

Zdroj: Journal of Neural Engineering; Jun2025, Vol. 22 Issue 3, p1-19, 19p

Computing Graph Neural Networks: A Survey from Algorithms to Accelerators.

Autoři: ABADAL, SERGI JAIN, AKSHAY GUIRADO, ROBERT a další

Zdroj: ACM Computing Surveys; Dec2022, Vol. 54 Issue 9, p1-38, 38p

Témata: ALGORITHMS, TELECOMMUNICATION systems

A Review of Neural Network-Based Image Noise Processing Methods.

Autoři: Volkov, Anton A. Kozlov, Alexander V. Cheremkhin, Pavel A. a další

Zdroj: Sensors (14248220); Oct2025, Vol. 25 Issue 19, p6088, 37p

Témata: CONVOLUTIONAL neural networks, DIGITAL image processing, SIGNAL filtering, AUTOENCODERS, ARTIFICIAL neural networks, GENERATIVE adversarial networks, IMAGE quality analysis

High-Resolution Daily XCH 4 Prediction Using New Convolutional Neural Network Autoencoder Model and Remote Sensing Data.

Autoři: Awad, Mohamad M. Homayouni, Saeid

Zdroj: Atmosphere; Jul2025, Vol. 16 Issue 7, p806, 18p

Témata: ATMOSPHERIC methane, CONVOLUTIONAL neural networks, ENVIRONMENTAL degradation, CLIMATE change, INTERPOLATION, ENVIRONMENTAL monitoring, REMOTE sensing

Implementation of Kolmogorov–Arnold Networks for Efficient Image Processing in Resource-Constrained Internet of Things Devices.

Autoři: Shaushenova, Anargul Kuznetsov, Oleksandr Nurpeisova, Ardak a další

Zdroj: Technologies (2227-7080); Apr2025, Vol. 13 Issue 4, p155, 21p

Témata: COMPUTER vision, INDUSTRIAL robots, CONVOLUTIONAL neural networks, IMAGE processing, COMPUTER networks, DEEP learning

Recent Landscape of Deep Learning Intervention and Consecutive Clustering on Biomedical Diagnosis.

Autoři: Mukherji, Ayan Mondal, Arindam Banerjee, Rajib a další

Zdroj: Artificial Intelligence & Applications (2811-0854); Oct2025, Vol. 3 Issue 4, p359-377, 19p

Témata: DEEP learning, DNA methylation, EPIGENETICS, MEDICAL informatics, METHYLATION, CLUSTER analysis (Statistics), DIAGNOSIS, ARTIFICIAL neural networks

Advancing Speech Enhancement with Generative Adversarial Network-Autoencoder: A Robust Adversarial Autoencoder Approach.

Autoři: Diwakar, Mandar Gupta, Brijendra

Zdroj: International Journal of Advanced Computer Science & Applications; 2025, Vol. 16 Issue 9, p326-332, 7p

A new architecture based resnet for steganography in color images.

Autoři: Hashemi, Seyed Hesam Odin Majidi, Mohammad-Hassan Khorashadizadeh, Saeed

Zdroj: Multimedia Tools & Applications; May2025, Vol. 84 Issue 16, p16229-16248, 20p

Témata: ARTIFICIAL neural networks, ARTIFICIAL intelligence, DEEP learning, AUTOENCODERS, FEATURE extraction, COLOR image processing

A Survey on Kolmogorov-Arnold Network.

Autoři: Somvanshi, Shriyank Javed, Syed Aaqib Islam, Md Monzurul a další

Zdroj: ACM Computing Surveys; Feb2026, Vol. 58 Issue 2, p1-35, 35p

Témata: ARTIFICIAL neural networks, QUESTIONNAIRES

Encoding Multivariate Time Series of Gas Turbine Data as Images to Improve Fault Detection Reliability.

Autoři: Losi, Enzo Venturini, Mauro Manservigi, Lucrezia a další

Zdroj: Machines; Oct2025, Vol. 13 Issue 10, p943, 42p

Témata: GAS turbines, FAULT diagnosis, CONVOLUTIONAL neural networks, IMAGE reconstruction, CONDITION-based maintenance, OUTLIER detection

Enhance real-time activity recognition of disabled individuals using hybridisation of convolutional neural network with attention mechanism.

Autoři: Alabdan, Rana AlAqil, Mohammed A. Alanazi, Eman M. a další

Zdroj: Signal, Image & Video Processing; Nov2025, Vol. 19 Issue 14, p1-15, 15p

Visible neural networks for multi-omics integration: a critical review.

Autoři: Selby, David Antony Jakhmola, Rashika Sprang, Maximilian a další

Zdroj: Frontiers in Artificial Intelligence; 2025, p1-17, 17p

A Hybrid Cnn-Lstm Approach For High-Accuracy Image Forgery Detection In Digital Forensics.

Autoři: Sardhara, Aarti Vekariya, Vipul Tadhani, Jaydeep

Zdroj: International Journal of Environmental Sciences (2229-7359); 2025 Special Issue, Vol. 11, p48-56, 9p

Témata: DIGITAL forensics, FORGERY, EDGE detection (Image processing), SIGNAL denoising, STATISTICAL accuracy, LONG short-term memory