Results 121 to 130 of about 129,070 (253)

Transformative skeletal motion analysis: optimization of exercise training and injury prevention through graph neural networks

Frontiers in Neuroscience
IntroductionExercise is pivotal for maintaining physical health in contemporary society. However, improper postures and movements during exercise can result in sports injuries, underscoring the significance of skeletal motion analysis. This research aims
Jiaju Zhu, Zijun Ye, Meixue Ren, Guodong Ma, Guodong Ma   +4 more
doaj   +1 more source

Image Denoising Using Quantum Deep Convolutional Generative Adversarial Network for Medical Images

International Journal of Computational Intelligence Systems
A significant role is played by medical images in diagnosing diseases and planning the course of treatment. Noise can potentially degrade the quality of images which can lead to misdiagnosis.
Priyanka Nandal, Sudesh Pahal, Govind Murari Upadhyay   +2 more
doaj   +1 more source

Towards Virtual H&E Staining of Hyperspectral Lung Histology Images Using Conditional Generative Adversarial Networks [PDF]

, 2017
Neslihan Bayramoğlu, Mika Kaakinen, Lauri Eklund, Janne Heikkilä   +3 more
openalex   +1 more source

Semi-supervised community detection method based on generative adversarial networks

Journal of King Saud University: Computer and Information Sciences
Community detection in complex networks often suffers from insufficient data and limited utilization of prior knowledge. In this paper we propose “Semi-supervised Generative Adversarial Network” (GANSE), a novel algorithm that integrates Generative ...
Xiaoyang Liu, Mengyao Zhang, Yanfei Liu, Chao Liu, Chaorong Li, Wei Wang, Xiaoqin Zhang, Asgarali Bouyer   +7 more
doaj   +1 more source

Generative Adversarial Networks and Other Generative Models

, 2023
AbstractGenerative networks are fundamentally different in their aim and methods compared to CNNs for classification, segmentation, or object detection. They have initially been meant not to be an image analysis tool but to produce naturally looking images.
openaire   +2 more sources

Advancing student outcome predictions through generative adversarial networks

Computers and Education: Artificial Intelligence
Predicting student outcomes is essential in educational analytics for creating personalised learning experiences. The effectiveness of these predictive models relies on having access to sufficient and accurate data. However, privacy concerns and the lack
Helia Farhood, Ibrahim Joudah, Amin Beheshti, Samuel Muller   +3 more
doaj   +1 more source

Face aging with conditional generative adversarial networks [PDF]

, 2017
Grigory Antipov, Moez Baccouche, Jean‐Luc Dugelay   +2 more
openalex   +1 more source

RETRACTED: Sankar et al. Utilizing Generative Adversarial Networks for Acne Dataset Generation in Dermatology. BioMedInformatics 2024, 4, 1059–1070

BioMedInformatics
The journal retracts the article, “Utilizing Generative Adversarial Networks for Acne Dataset Generation in Dermatology” [...]
Aravinthan Sankar, Kunal Chaturvedi, Al-Akhir Nayan, Mohammad Hesam Hesamian, Ali Braytee, Mukesh Prasad   +5 more
doaj   +1 more source

Statistical parametric speech synthesis using generative adversarial networks under a multi-task learning framework [PDF]

, 2017
Shan Yang, Lei Xie, Xiao Dong Chen, Xiaoyan Lou, Xuan Zhu, Dongyan Huang, Haizhou Li   +6 more
openalex   +1 more source

Robustness of Generative Adversarial CLIPs Against Single-Character Adversarial Attacks in Text-to-Image Generation

IEEE Access
Generative Adversarial Networks (GANs) have emerged as a powerful type of generative model, particularly effective at creating images from textual descriptions.
Patibandla Chanakya, Putla Harsha, Krishna Pratap Singh   +2 more
doaj   +1 more source