Results 151 to 160 of about 16,046 (295)

Towards Modeling Geographical Processes with Generative Adversarial Networks (GANs) (Short Paper)

, 2019
Recently, Generative Adversarial Networks (GANs) have demonstrated great potential for a range of Machine Learning tasks, including synthetic video generation, but have so far not been applied to the domain of modeling geographical processes.
Jonietz, David, Kopp, Michael
core   +1 more source

Feasibility and Reproducibility of a Structure‐Guided Deep Learning Model for Automatic Detection of the Standard Sagittal Plane in First‐Trimester Nuchal Translucency Assessment Using 3D Ultrasound

Journal of Ultrasound in Medicine, EarlyView.
Objectives Accurate nuchal translucency (NT) measurement for assessing the risk of fetal genetic abnormalities requires precise acquisition of the mid‐sagittal plane (MSP). However, achieving an appropriate MSP is technically challenging due to anatomical variability and operator dependence inherent in conventional 2‐dimensional (2D) ultrasound.
Hayan Kwon, Hyewon Hur, Hyun Cheol Cho, Yun ji Jung, Suhra Kim, Ja‐Young Kwon   +5 more
wiley   +1 more source

Exploring deep generative models for improved data generation in hypertrophic cardiomyopathy

Ingenius: Revista de Ciencia y Tecnología
Data generation strategies are essential for addressing the challenge of limited training data in deep learning-based medical image analysis, particularly for hypertrophic cardiomyopathy (HCM) using magnetic resonance imaging (MRI).
Swarajya Madhuri Rayavarapu, Gottapu Sasibhushana Rao   +1 more
doaj   +1 more source

Denoising of ASL Data Using Deep Learning Priors Generated From Distribution Remapping

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop an effective deep learning (DL)–based method to denoise arterial spin labeling (ASL) data. Methods Conventional DL–based ASL denoising methods often suffer from overfitting and poor generalization when training data are limited.
Ziyang Xu, Rong Guo, Ziwen Ke, Yudu Li, Yibo Zhao, Wen Jin, Ruihao Liu, Ziyu Meng, Yao Li, Zhi‐Pei Liang   +9 more
wiley   +1 more source

Boosting Deep Feature Fusion-Based Detection Model for Fake Faces Generated by Generative Adversarial Networks for Consumer Space Environment

IEEE Access
In the consumer space, deep fakes refer to highly realistic, AI-generated images, audio, or videos that mimic real people generated by cutting-edge technologies such as Generative Adversarial Networks (GANs). In the digital age, recognizing and detecting
Fadwa Alrowais, Asma Abbas Hassan, Wafa Sulaiman Almukadi, Meshari H. Alanazi, Radwa Marzouk, Ahmed Mahmud   +5 more
doaj   +1 more source

Enhancing Rock Strength Prediction and Features Selection by Coupling Well Log Data and Deep Learning Approaches in Reservoir Geomechanics

International Journal for Numerical and Analytical Methods in Geomechanics, EarlyView.
ABSTRACT Accurate rock strength parameters play a vital role in petroleum and mining operations for sustainable drilling activities, and wellbore stability analysis. This study investigates the applicability of deep learning techniques for assessing data‐driven models, and to conduct parametric sensitivity examination for feature attributes ranking to ...
Mohammad Islam Miah, Md. Shakil Rahaman, Travis Wiens   +2 more
wiley   +1 more source

A Generative Adversarial Network (GAN) Fingerprint Approach Over LTE

IEEE Access
Recent advancements in communication technologies have significantly enhanced localization techniques, improving both accuracy and operating modes. Initially, localization methods relied on global navigation satellite systems, offering high accuracy but proving inefficient in Non-Line-of-Sight scenarios.
Luigi Serreli, Mauro Fadda, Roberto Girau, Pietro Ruiu, Daniele D. Giusto, Matteo Anedda   +5 more
openaire   +3 more sources

Conditional Generative Modeling for Enhanced Credit Risk Management in Supply Chain Finance

Naval Research Logistics (NRL), EarlyView.
ABSTRACT The rapid expansion of cross‐border e‐commerce (CBEC) has created significant opportunities for small‐ and medium‐sized sellers, yet financing remains a critical challenge due to their limited credit histories. Third‐party logistics (3PL)‐led supply chain finance (SCF) has emerged as a promising solution, leveraging in‐transit inventory as ...
Qingkai Zhang, L. Jeff Hong, Houmin Yan
wiley   +1 more source

The transformative potential of artificial intelligence in pediatric medicine: Current applications, methodological challenges, and future directions

Pediatric Investigation, EarlyView.
Artificial intelligence (AI) offers transformative potential for paediatric diagnosis and treatment, yet implementation faces unique challenges, including data scarcity, algorithmic bias, and children's developmental physiology. This review examines current applications and charts a path toward transparent, equitable, and trustworthy AI in child health.
Ruisong Wang, Xiaoman Ding, Wanyue Zhang, Tieliu Shi   +3 more
wiley   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

Responsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen, Siwei Yang, Xiangqian Cui, Ziheng Liu, Hang Wang, Yongqiang Li, Peng He, Miao Wang, Guqiao Ding   +8 more
wiley   +1 more source