Results 141 to 150 of about 39,632 (294)

Pix2Pix generative-adversarial network in improving the quality of T2-weighted prostate magnetic resonance imaging: a multi-reader study [PDF]

PURPOSE: To assess the performance and feasibility of generative deep learning in enhancing the image quality of T2-weighted (T2W) prostate magnetic resonance imaging (MRI).
İlkay Öksüz, Sabri Şirolu, Nurper Denizoğlu, Mustafa Said Kartal, Deniz Alis, Müjgan Orman, Serpil Kurtcan, Ercan Karaarslan, Delal Seker, Yeliz Başar, Mustafa Ege Seker, Aydan Arslan   +11 more
core   +1 more source

Ensembles of Generative Adversarial Networks

CoRR, 2016
accepted NIPS 2016 Workshop on Adversarial ...
Yaxing Wang, Lichao Zhang 0001, Joost van de Weijer 0001   +2 more
openaire   +2 more sources

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

Advanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser, Haseeb Muhammad, Junaid Younas, Gillian Lovell, Bianca Migliori, Andreas Dengel, Sheraz Ahmed   +6 more
wiley   +1 more source

Pulsar identification based on generative adversarial network and residual network

, 2022
The search for pulsars is an important area of study in modern astronomy. The amount of collected pulsar data is increasing exponentially as the performance of modern radio telescopes improves, necessitating the improvement of the original pulsar search ...
Xu, Yang, Yin, Qian, Bao, Zelun, Zhang, Zifeng, Liu, Guiru, Xie, Yanxi, Li, Yefan, Zheng, Xin   +7 more
core  

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Generative modelling and adversarial learning [PDF]

, 2018
University of Technology Sydney. Faculty of Engineering and Information Technology.A main goal of statistics and machine learning is to represent and manipulate high-dimensional probability distributions of real-world data, such as natural images ...
Wang, Chaoyue
core  

Epistemic Generative Adversarial Networks

CoRR
Generative models, particularly Generative Adversarial Networks (GANs), often suffer from a lack of output diversity, frequently generating similar samples rather than a wide range of variations. This paper introduces a novel generalization of the GAN loss function based on Dempster-Shafer theory of evidence, applied to both the generator and ...
Muhammad Mubashar, Fabio Cuzzolin
openaire   +2 more sources

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

The Pose Correction of Badminton Stroke Using Generative Adversarial Network

, 2022
This thesis developed a system for the badminton strokes correction, including serve, smash, and clear. The purpose of this framework is to allow users to improve their badminton skills using mobile devices at hand.
Cai, Wen-Chen
core