Výsledky vyhledávání - hybrid deep conventional autoencoder~

Hybrid Deep Learning Framework for Anomaly Detection in Power Plant Systems.

Autoři: Wang, Shuchong Zhao, Changxiang Liu, Xingchen a další

Zdroj: Algorithms. Nov2025, Vol. 18 Issue 11, p704. 18p.

Témata: *AUTOENCODERS, *TRANSFORMER models, *ENSEMBLE learning, *OUTLIER detection, *ELECTRIC power plants, *GAUSSIAN mixture models

EmotionNet: A Novel Hybrid Deep Learning Model for Arabic Speech Emotion Recognition.

Autoři: Belhadj, Mourad Mazouz, Mihoub Djeridi, Dalal

Zdroj: Engineering, Technology & Applied Science Research; Oct2025, Vol. 15 Issue 5, p26619-26625, 7p

Témata: EMOTION recognition, DEEP learning, FEATURE extraction, AUTOENCODERS

Forecasting gold price using hybrid deep neural network LSTM-autoencoder.

Autoři: Saini, Agampreet Singh, Rahul Kumar Sinha, Puneet

Zdroj: Discover Artificial Intelligence; 10/22/2025, Vol. 5 Issue 1, p1-19, 19p

Témata: FORECASTING, LONG short-term memory, GOLD sales & prices, DEEP learning, ECONOMIC forecasting, AUTOENCODERS

A Hybrid Deep Learning Model for E‐Commerce Recommendations: Sentiment Analysis With Autoencoders and Generative Adversarial Networks.

Autoři: Yarjanli, Mohammad Mahdinasab, Neda Murray, Richard

Zdroj: International Journal of Intelligent Systems; 10/2/2025, Vol. 2025, p1-36, 36p

Témata: SENTIMENT analysis, DEEP learning, GENERATIVE adversarial networks, FEATURE extraction, ELECTRONIC commerce, AUTOENCODERS

Autoencoder-Assisted Stacked Ensemble Learning for Lymphoma Subtype Classification: A Hybrid Deep Learning and Machine Learning Approach.

Autoři: Ogundokun, Roseline Oluwaseun Owolawi, Pius Adewale Tu, Chunling a další

Zdroj: Tomography: A Journal for Imaging Research; Aug2025, Vol. 11 Issue 8, p91, 22p

Témata: AUTOENCODERS, ENSEMBLE learning, DEEP learning, FEATURE extraction, CANCER diagnosis, HISTOPATHOLOGY, MACHINE learning

Intelligent Intrusion Detection System Against Various Attacks Based on a Hybrid Deep Learning Algorithm.

Autoři: Susilo, Bambang Muis, Abdul Sari, Riri Fitri

Zdroj: Sensors (14248220); Jan2025, Vol. 25 Issue 2, p580, 26p

Témata: CONVOLUTIONAL neural networks, LONG short-term memory, MACHINE learning, CYBERTERRORISM, AUTOENCODERS, INTRUSION detection systems (Computer security), DEEP learning

An Intelligent Recommendation System Utilizing a Hybrid Deep Learning Method.

Autoři: Tholib, Abu Widiyaningtyas, Triyanna Prasetya, Didik Dwi

Zdroj: Engineering, Technology & Applied Science Research; Aug2025, Vol. 15 Issue 4, p25971-25977, 7p

Témata: RECOMMENDER systems, LONG short-term memory, MATRIX decomposition, DATA quality, USER experience, ENSEMBLE learning, AUTOENCODERS

Enhanced Product Defect Detection in Smart Manufacturing Using ConvNeXt-Stacked Autoencoder Architecture.

Autoři: Hasan, Ahmed M. Nasser, Ahmed R. Al-Araji, Ahmed Sabah a další

Zdroj: Indonesian Journal of Science & Technology; Sep2025, Vol. 10 Issue 2, p297-316, 20p

Témata: CONVOLUTIONAL neural networks, MACHINE learning, MANUFACTURING defects, AUTOENCODERS, QUALITY control, DEEP learning

Hybrid Deep Learning Model for Hippocampal Localization in Alzheimer's Diagnosis Using U-Net and VGG16.

Autoři: Najjar, Fallah H. Hassan, Nawar Banwan Kadum, Salman Abd

Zdroj: International Journal of Robotics & Control Systems; 2025, Vol. 5 Issue 2, p730-747, 18p

Témata: ALZHEIMER'S disease, DATA augmentation, AUTOENCODERS, NEURODEGENERATION, IMAGE analysis

Performing Hybrid Spectrum Sensing with an Adaptive and Attentive Multi-stacked Deep Learning Network in a Cognitive Radio Network.

Autoři: Koteswara Rao, R. Sahaai, Madona B. Sharanya, C.

Zdroj: Journal of Information & Knowledge Management. Aug2025, Vol. 24 Issue 4, p1-36. 36p.

Témata: *Real-time computing, Cognitive radio, Deep learning, Mathematical optimization, Convolutional neural networks, Signal detection, Long short-term memory

ACXNet hybrid deep learning model for cross task mental workload estimation using EEG neural manifolds.

Autoři: Abinaya, G. Dinakaran, K.

Zdroj: Scientific Reports; 10/8/2025, Vol. 15 Issue 1, p1-22, 22p

Témata: ELECTROENCEPHALOGRAPHY, DEEP learning, COGNITIVE psychology, CLASSIFICATION algorithms, COGNITIVE load, FEATURE extraction, NEUROSCIENCES

Enhanced Copy-Move Forgery Detection in Images Using Hybrid Deep Learning Approach.

Autoři: Gholap, Bhushan Deshmukh, Monika

Zdroj: EPJ Web of Conferences; 11/20/2025, Vol. 341, p1-10, 10p

Témata: DEEP learning, FORGERY, RECURRENT neural networks, TRANSFORMER models, PHOTOGRAPHIC editing, SIGNAL detection

A Robust Disease Prediction System Using Hybrid Deep Neural Networks.

Autoři: Tharageswari, K. Sundaram, N. Mohana Santhosh, R.

Zdroj: Journal of Cybersecurity & Information Management; 2025, Vol. 16 Issue 1, p107-119, 13p

Témata: ARTIFICIAL neural networks, MEDICAL care costs, FEATURE selection, ACUTE diseases, MEDICAL records

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

A hybrid 1DCNN-GRU deep learning framework for classifying caprine granulosa cell fertility potential using single-cell transcriptomics.

Autoři: Sananmuang, Thanida Puthier, Denis Chokeshaiusaha, Kaj

Zdroj: Veterinary World. Jul2025, Vol. 18 Issue 7, p1922-1935. 14p.

Témata: Granulosa cells, Fertility, Convolutional neural networks, Transcriptomes, Deep learning, Recurrent neural networks, Goats, Biomarkers

Hybrid Deep Learning Models for Analyzing Histological Images of the Zebrafish Intestine Under Oxidative Stress.

Autoři: Pavel, Cristian Dan Moldovanu, Simona Pavel, Irina Andreea a další

Zdroj: Diagnostics (2075-4418); Nov2025, Vol. 17 Issue 22, p2859, 16p

Témata: OXIDATIVE stress, CONVOLUTIONAL neural networks, ZEBRA danio, DEEP learning, IMAGE enhancement (Imaging systems), ARTIFICIAL intelligence, HISTOPATHOLOGY, CLASSIFICATION

Hybrid Deep Learning for Fault Diagnosis in Photovoltaic Systems.

Autoři: Bougoffa, Mouaad Benmoussa, Samir Djeziri, Mohand a další

Zdroj: Machines; May2025, Vol. 13 Issue 5, p378, 18p

Témata: CLEAN energy, SUSTAINABILITY, PHOTOVOLTAIC power systems, ENERGY infrastructure, AUTOENCODERS, DEEP learning

Fraudulent account detection in social media using hybrid deep transformer model and hyperparameter optimization.

Autoři: Shukla, Prashant Kumar Veerasamy, Bala Dhandayuthapani Alduaiji, Noha a další

Zdroj: Scientific Reports; 11/3/2025, Vol. 15 Issue 1, p1-23, 23p

Témata: SOCIAL media, DEEP learning, TRANSFORMER models, DATA augmentation, GENERATIVE adversarial networks, FRAUD

Enhanced Hybrid Deep Learning Models-Based Anomaly Detection Method for Two-Stage Binary and Multi-Class Classification of Attacks in Intrusion Detection Systems.

Autoři: Kamal, Hesham Mashaly, Maggie

Zdroj: Algorithms; Feb2025, Vol. 18 Issue 2, p69, 59p

Témata: COMPUTER network traffic, AUTOENCODERS, ANOMALY detection (Computer security), TRANSFORMER models, MACHINE learning, DEEP learning

Hybrid Deep Reinforcement Learning for High Volatility Windows Prediction with Advanced Feature Extraction.

Autoři: Casares, A. J. Martínez

Zdroj: Journal of Financial Data Science; Fall2025, Vol. 7 Issue 4, p107-130, 24p

Témata: MARKET volatility, FEATURE extraction, STATISTICAL measurement, REINFORCEMENT learning