Results 171 to 180 of about 116,908 (254)

Generative adversarial network

, 2019
Matt Adams, Arlene Campos, Dimitrios Toumpanakis   +2 more
openaire   +1 more source

Prediction of Pipeline Defect Depth and Classification Based on CatBoost

Energy Science &Engineering, EarlyView.
Obtaining detection data using in‐line pipeline inspection, the synthetic minority oversampling technique (SMOTE) is applied to expand the sample set, thereby increasing the number of minority‐class samples. This approach effectively improves minority‐class detection and enhances pipeline safety assessment. ABSTRACT Magnetic flux leakage detection is a
Cong Chen, Rui Li, Guanwei Jia, Dongcun Qin   +3 more
wiley   +1 more source

Generative Adversarial Networks for Modeling Bio-Electric Fields in Medicine: A Review of EEG, ECG, EMG, and EOG Applications. [PDF]

Bioengineering (Basel)
Liang J, Zhou Y, Ma K, Jia Y, Zhang Y, Han B, Xiang M.   +6 more
europepmc   +1 more source

Application of GAN–CNN in Risk Assessment of Pipeline Failures in Multiphase Pipeline With Image Information Encoding Approach

Energy Science &Engineering, EarlyView.
Field data from multiphase pipelines are transformed into grayscale images via Image Information Encoding, preserving feature values and interparameter relationships. A GAN–CNN model generates synthetic images that are decoded to expand the original database.
Sihang Chen, Na Zhang, Biyuan Shui
wiley   +1 more source

Towards an optimized paradigm: generative adversarial networks and 3D modeling in landscape design and generation. [PDF]

PLoS One
He M.
europepmc   +1 more source

A Review of Overcurrent Protection in Smart Grids Under Cyber‐Physical Threats With a Cyber‐Physical Evaluation Framework

Energy Science &Engineering, EarlyView.
By manipulating current and voltage measurements, an assailant can induce unwanted relay action while attempting to avoid detection. Detecting advanced cyber intrusions in power protection environments requires specialised data analysis and anomaly detection methods.
Feras Alasali, Anas AlMajali, Naser Naily, Hassen Loukil, Salah AbuGhalyon, William Holderbaum, Abdelaziz Salah Saidi   +6 more
wiley   +1 more source

Dynamic Contrast-enhanced MRI for Evaluating Breast Cancer Chemotherapy Response Using Conditional Generative Adversarial Networks. [PDF]

Radiol Imaging Cancer
Arledge CA, Zhao AH, Topaloglu U, Zhao D.   +3 more
europepmc   +1 more source

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source

Detection of unseen malware threats using generative adversarial networks and deep learning models. [PDF]

Sci Rep
Joshi C, Kumar J, Kumawat G.
europepmc   +1 more source

Improving Implied Volatility Forecasts for American Options Using Neural Networks

Journal of Futures Markets, EarlyView.
ABSTRACT This paper explores the application of neural networks to improve pricing of American options. Focusing on both American and European options on the S&P 100 index from January 2016 to August 2023, we integrate neural networks to model the difference between market‐implied and model‐implied volatilities derived from the Black‐Scholes and Heston
Haitong Jiang, Emese Lazar, Miriam Marra
wiley   +1 more source