Results 191 to 200 of about 16,046 (295)

Single Line Drawing Generation via Semantics‐Driven Optimization

Computer Graphics Forum, EarlyView.
We present a method for automatically generating single‐line drawings in vector format, guided by a text prompt or an input image. Our approach leverages score distillation sampling to optimize the parameters of a uniform rational B‐spline (URBS) curve, ensuring that the drawing consists of a single continuous stroke by design.
Tanguy Magne, Alexandre Binninger, Ruben Wiersma, Olga Sorkine‐Hornung   +3 more
wiley   +1 more source

From Pixels to Precision: Generative Artificial Intelligence as a Paradigm Shift in Spine Imaging-Technical Foundations, Clinical Applications, and the Path to Safe Clinical Deployment. [PDF]

Neurospine
Ashraf D, Sanker V, Liverani L, Park C, Medikonda RT, Cavagnaro MJ, Jeon I, Ratliff J, Desai A.   +8 more
europepmc   +1 more source

Textile and colour defect detection using deep learning methods

Coloration Technology, EarlyView.
Abstract Recent advances in deep learning (DL) have significantly enhanced the detection of textile and colour defects. This review focuses specifically on the application of DL‐based methods for defect detection in textile and coloration processes, with an emphasis on object detection and related computer vision (CV) tasks.
Hao Cui, Abdel‐Fattah Seyam, Renzo Shamey   +2 more
wiley   +1 more source

Generative Adversarial Networks for Intrusion Detection Systems: A Comprehensive Survey of Applications, Challenges, and Research Directions. [PDF]

Arab J Sci Eng
Alauthman M, Aslam N, Al-Qerem A, Aldweesh A, Sureephong P.   +4 more
europepmc   +1 more source

Risk Management with Feature-Enriched Generative Adversarial Networks (FE-GAN)

This paper investigates the application of Feature-Enriched Generative Adversarial Networks (FE-GAN) in financial risk management, with a focus on improving the estimation of Value at Risk (VaR) and Expected Shortfall (ES).
Chen, Ling
core  

Toward a Synthetic Data Revolution: Diffusion Model‐Enhanced Hepatocellular Carcinoma Prediction in Steatotic Liver Disease

Hepatology Research, EarlyView.
ABSTRACT Aim Steatotic liver disease (SLD) encompasses a heterogeneous spectrum with varying risks of hepatocellular carcinoma (HCC). Limited sample sizes limit the development of predictive models, particularly for rare outcomes. This study evaluated whether generative artificial intelligence (AI)‐based synthetic data augmentation can enhance HCC risk
Masaya Sato, Takuma Nakatsuka, Yuki Matsushita, Takuma Kaneko, Keisuke Mabuchi, Tomoharu Yamada, Kazuya Okushin, Tatsuya Minami, Yotaro Kudo, Satoshi Kodera, Kazuhiko Koike, Mitsuhiro Fujishiro, Ryosuke Tateishi   +12 more
wiley   +1 more source

Generative models and synthetic data in clinical prediction models: Promoting consistency, reproducibility, and transparency. [PDF]

J Clin Transl Sci
Mangino AA, Ahmed T, Sorrell VL.
europepmc   +1 more source

Generative Artificial Intelligence for Computer Vision in Endodontics: A Review of Current State and Future Potential

International Endodontic Journal, EarlyView.
ABSTRACT Background Computer vision methods based on artificial intelligence (AI) have found numerous applications in endodontic diagnosis and treatment planning. While most current applications employ discriminative deep learning models for detection and classification tasks, the field is now witnessing the rise of generative AI (GenAI), a class of AI
Hossein Mohammad‐Rahimi, Sanyam Jain, Khuram Naveed, Sepanta Hosseinpour, Lise‐Lotte Kirkevang, Ali Nosrat, Ruben Pauwels   +6 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