Results 101 to 110 of about 43,961 (294)

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source

A Deep Learning-Based Two-Branch Generative Adversarial Network for Image De-Raining

Sensors
Raindrops can scatter and absorb light, causing images to become blurry or distorted. To improve image quality by reducing the impact of raindrops, this paper proposes a novel generative adversarial network for image de-raining. The network comprises two
Liquan Zhao, Jie Long, Tie Zhong
doaj   +1 more source

Denoising of pre-beamformed photoacoustic data using generative adversarial networks

, 2021
Amir Refaee, Corey J. Kelly, Hamid Moradi, Septimiu E. Salcudean   +3 more
openalex   +1 more source

Cognitive Covert Traffic Synthesis Method Based on Generative Adversarial Network [PDF]

, 2021
Zhangguo Tang, Junfeng Wang, Huanzhou Li, Jian Zhang, Junhao Wang   +4 more
openalex   +1 more source

Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces

Advanced Intelligent Discovery, EarlyView.
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali, Lachlan Caulfield, Eric Sauter, Alexei Nefedov, Chengwu Yang, Christof Wöll   +5 more
wiley   +1 more source

CWGAN-GP with residual network model for lithium-ion battery thermal image data expansion with quantitative metrics

Energy and AI
Lithium batteries find extensive applications in energy storage. Temperature is a crucial indicator for assessing the state of lithium-ion batteries, and numerous experiments require thermal images of lithium-ion batteries for research purposes. However,
Fengshuo Hu, Chaoyu Dong, Luyu Tian, Yunfei Mu, Xiaodan Yu, Hongjie Jia   +5 more
doaj   +1 more source

Hamiltonian quantum generative adversarial networks

Physical Review Research
We propose Hamiltonian quantum generative adversarial networks (HQuGANs) to learn to generate unknown input quantum states using two competing quantum optimal controls. The game-theoretic framework of the algorithm is inspired by the success of classical generative adversarial networks in learning high-dimensional distributions.
Leeseok Kim, Seth Lloyd, Milad Marvian
openaire   +3 more sources

Image generations techniques using Generative adversarial networks

Adaptivni Sistemi Avtomatičnogo Upravlinnâ, 2023
The object of research is image generation algorithms based on GAN. The article reviews the main uses of these networks for image generation and main types of such algorithms, which can be used for this. Generative Adversarial Networks (GANs) have been a significant breakthrough in machine learning, allowing the generation of images that are ...
Ivanov, A., Onyshchenko, V.
openaire   +2 more sources

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Conditional noise generative adversarial networks with Siamese neural network for longer time series forecasting

Scientific Reports
Generative adversarial networks have achieved strong results in computer vision, but their use in time series forecasting remains limited. This paper proposes a conditional noise generative adversarial network with a Siamese neural network as ...
Haotian Mao, Xiao Feng
doaj   +1 more source