Results 111 to 120 of about 16,046 (295)
Using GANs (Generative Adversarial Networks) to generate fake patients
, 2020 This master thesis is a continuation of the investigation line opened in with the Generative Adversarial Network based Machine for Fake Data Generation thesis.
Guarner Escribano, Álvaro
core +1 more source
Evolution and Breakthroughs of Generative Adversarial Network Technology [PDF]
ITM Web of ConferencesGenerative Adversarial Networks (GANs) have significantly evolved since their introduction, continually adapting through theoretical and architectural innovations to remain a vibrant research area in generative AI.
Wang Yiding
doaj +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
CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Autonomous vehicles are required to operate in an uncertain environment. Recent advances in computational intelligence techniques make it possible to understand driving scenes in various environments by using a semantic segmentation neural network, which assigns a class label to each pixel.
Yining Hua +4 more
wiley +1 more source
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
Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy
Advanced Intelligent Discovery, EarlyView.Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang +9 more
wiley +1 more source
A Review on Domain Adaption and Generative Adversarial Networks(GANs)
CoRRThe major challenge in today's computer vision scenario is the availability of good quality labeled data. In a field of study like image classification, where data is of utmost importance, we need to find more reliable methods which can overcome the scarcity of data to produce results comparable to previous benchmark results.
Aashish Dhawan, Divyanshu Mudgal
openaire +2 more sources
Ultrasound breast images denoising using generative adversarial networks (GANs)
[EN] Ultrasound in conjunction with mammography imaging, plays a vital role in the early detection and diagnosis of breast cancer. However, speckle noise affects medical ultrasound images and degrades visual radiological interpretation.
Jimenez-Gaona, Yuliana +5 more
core +1 more source
Clinical data sharing using Generative Adversarial Networks
, 2022 Obtaining data is challenging for researchers, especially when it comes to medical data. Moreover, using medical data as there are concerns about privacy and confidentiality issues requires specific considerations.
Ayyoubzadeh, Seyed Mehdi +2 more
core
Advanced Intelligent Discovery, EarlyView.Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source