Results 71 to 80 of about 221,929 (334)
Advanced Functional Materials, EarlyView.AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu +5 more
wiley +1 more source
Generative Adversarial Networks GAN Overview
Jisuanji kexue yu tansuo, 2020 As a new unsupervised learning algorithm framework, generative adversarial networks (GAN) has been favored by more and more researchers, and it has become a research hotspot. GAN is inspired by the two-person zero-sum game theory in game theory.
LIANG Junjie, WEI Jianjing, JIANG Zhengfeng
doaj +1 more source
Generative Adversarial Networks in finance: an overview
, 2021 Modelling in finance is a challenging task: the data often has complex statistical properties and its inner workings are largely unknown. Deep learning algorithms are making progress in the field of data-driven modelling, but the lack of sufficient data to train these models is currently holding back several new applications.
Eckerli, Florian, Osterrieder, Joerg
openaire +3 more sources
Advanced Functional Materials, EarlyView.Advances in integrating artificial intelligence into 3D bioprinting are systematically reviewed here. Machine learning, computer vision, robotics, natural language processing, and expert systems are examined for their roles in optimizing bioprinting parameters, real‐time monitoring, quality control, and predictive maintenance.
Joao Vitor Silva Robazzi +10 more
wiley +1 more source
Beautification of images by generative adversarial networks
Journal of Vision, 2023 Finding the properties underlying beauty has always been a prominent yet difficult problem. However, new technological developments have often aided scientific progress by expanding the scientists' toolkit. Currently in the spotlight of cognitive neuroscience and vision science are deep neural networks.
Music, Amar +2 more
openaire +2 more sources
Advanced Functional Materials, EarlyView.This review discusses cellulose‐based hydrogels technology, analyzes their application progress in physiological signal monitoring, and explores the effects of pretreatment, crosslinking, and molding methods on gel performance, to provide valuable insights into the efficient utilization of plant fibers and the environmentally friendly development of ...
Zhiming Wang +8 more
wiley +1 more source
Mathematics, 2023 In this paper, we propose a novel network, self-attention generative adversarial network with blur and memory (BaMSGAN), for generating anime faces with improved clarity and faster convergence while retaining the capacity for continuous learning ...
Xu Li +4 more
doaj +1 more source
Super-Resolution for Overhead Imagery Using DenseNets and Adversarial Learning
, 2017 Recent advances in Generative Adversarial Learning allow for new modalities of image super-resolution by learning low to high resolution mappings.
Bosch, Marc +2 more
core +1 more source
Advanced Materials, EarlyView.This review summarizes the latest progress in transforming renewable bamboo resources into high‐value functional materials. It emphasizes how to leverage bamboo's multiscale hierarchical structures to realize innovative applications in energy, construction, environment, and medicine, providing key insights for developing high‐performance bio‐based ...
Yuxiang Huang +13 more
wiley +1 more source
Image Colorization with Generative Adversarial Networks
, 2018 Over the last decade, the process of automatic image colorization has been of significant interest for several application areas including restoration of aged or degraded images. This problem is highly ill-posed due to the large degrees of freedom during
Ebrahimi, Mehran +2 more
core +1 more source