Results 31 to 40 of about 219,974 (297)

DRB-GAN: A Dynamic ResBlock Generative Adversarial Network for Artistic Style Transfer [PDF]

IEEE International Conference on Computer Vision, 2021
The paper proposes a Dynamic ResBlock Generative Adversarial Network (DRB-GAN) for artistic style transfer. The style code is modeled as the shared parameters for Dynamic ResBlocks connecting both the style encoding network and the style transfer network.
Wenju Xu, Chengjiang Long, Ruisheng Wang, Guanghui Wang   +3 more
semanticscholar   +1 more source

Designing optimized drug candidates with Generative Adversarial Network

Journal of Cheminformatics, 2022
Drug design is an important area of study for pharmaceutical businesses. However, low efficacy, off-target delivery, time consumption, and high cost are challenges and can create barriers that impact this process.
Maryam Abbasi, Beatriz P. Santos, Tiago O. Pereira, Raul Sofia, Nelson R. C. Monteiro, Carlos J. V. Simões, Rui M. M. Brito, B. Ribeiro, J. L. Oliveira, Joel P. Arrais   +9 more
semanticscholar   +1 more source

HGAN: Hybrid generative adversarial network [PDF]

Journal of Intelligent & Fuzzy Systems, 2021
In this paper, we present a simple approach to train Generative Adversarial Networks (GANs) in order to avoid a mode collapse issue. Implicit models such as GANs tend to generate better samples compared to explicit models that are trained on tractable data likelihood.
Iranmanesh, Seyed Mehdi, Nasrabadi, Nasser M.   +1 more
openaire   +2 more sources

DuCaGAN: Unified Dual Capsule Generative Adversarial Network for Unsupervised Image-to-Image Translation

IEEE Access, 2020
With the appearance of Generative Adversarial Network (GAN), image-to-image translation based on a new unified framework has attracted growing interests.
Guifang Shao, Meng Huang, Fengqiang Gao, Tundong Liu, Liduan Li   +4 more
doaj   +1 more source

Generating synthesized computed tomography from CBCT using a conditional generative adversarial network for head and neck cancer patients

Technology in Cancer Research & Treatment, 2022
Purpose: To overcome the imaging artifacts and Hounsfield unit inaccuracy limitations of cone-beam computed tomography, a conditional generative adversarial network is proposed to synthesize high-quality computed tomography-like images from cone-beam ...
Yun Zhang PhD, Sheng-gou Ding MD, Xiao-chang Gong MD, Xing-xing Yuan MD, Jia-fan Lin MD, Qi Chen MD, Jin-gao Li MD, PhD   +6 more
doaj   +1 more source

PHom-GeM: Persistent Homology for Generative Models [PDF]

, 2019
Generative neural network models, including Generative Adversarial Network (GAN) and Auto-Encoders (AE), are among the most popular neural network models to generate adversarial data.
Charlier, Jeremy, Hilger, Jean, State, Radu   +2 more
core   +2 more sources

Multi‐style Chinese art painting generation of flowers

IET Image Processing, 2021
With the proposal and development of Generative Adversarial Networks, the great achievements in the field of image generation are made. Meanwhile, many works related to the generation of painting art have also been derived. However, due to the difficulty
Feifei Fu, Jiancheng Lv, Chenwei Tang, Mao Li   +3 more
doaj   +1 more source

High-fidelity reconstruction of turbulent flow from spatially limited data using enhanced super-resolution generative adversarial network [PDF]

The Physics of Fluids, 2021
In this study, a deep learning-based approach is applied with the aim of reconstructing high-resolution turbulent flow fields using minimal flow fields data. A multi-scale enhanced super-resolution generative adversarial network with a physics-based loss
M. Yousif, Linqi Yu, Heechang Lim
semanticscholar   +1 more source

A Review of GAN-Based Super-Resolution Reconstruction for Optical Remote Sensing Images

Remote Sensing, 2023
High-resolution images have a wide range of applications in image compression, remote sensing, medical imaging, public safety, and other fields. The primary objective of super-resolution reconstruction of images is to reconstruct a given low-resolution ...
Xuan Wang, Lijun Sun, Abdellah Chehri, Yongchao Song   +3 more
doaj   +1 more source

Generative Adversarial Networks in Retinal Image Classification

Applied Sciences, 2023
The recent introduction of generative adversarial networks has demonstrated remarkable capabilities in generating images that are nearly indistinguishable from real ones.
Francesco Mercaldo, Luca Brunese, Fabio Martinelli, Antonella Santone, Mario Cesarelli   +4 more
doaj   +1 more source