Results 21 to 30 of about 219,883 (315)

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

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

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

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

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

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

COVID-19 CT Image Synthesis With a Conditional Generative Adversarial Network [PDF]

IEEE journal of biomedical and health informatics, 2020
Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic that has spread rapidly since December 2019. Real-time reverse transcription polymerase chain reaction (rRT-PCR) and chest computed tomography (CT) imaging both play an important role in ...
Yifan Jiang, Han Chen, M. Loew, Hanseok Ko   +3 more
semanticscholar   +1 more source

An Adaptive Generative Adversarial Network for Cardiac Segmentation from X-ray Chest Radiographs

Applied Sciences, 2020
Medical image segmentation is a classic challenging problem. The segmentation of parts of interest in cardiac medical images is a basic task for cardiac image diagnosis and guided surgery.
Xiaochang Wu, Xiaolin Tian
doaj   +1 more source

Application of deep learning in recognition of accrued earnings management

Heliyon, 2023
We choose the sample data in Chinese capital market to compare the measurement effect of earnings management with Deep Belief Network, Deep Convolution Generative Adversarial Network, Generalized Regression Neural Network and modified Jones model by ...
Jia Li, Zhoutianyang Sun
doaj   +1 more source