Results 121 to 130 of about 124,232 (320)

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

Transfer Learning and Permutation‐Invariance Improving Predicting Genome‐Wide, Cell‐Specific and Directional Interventions Effects of Complex Systems

Advanced Science, EarlyView.
SETComp, a transfer learning model based on permutation‐invariance, is pre‐trained on single‐compound intervention data and fine‐tuned on complex system (e.g., natural products) data. The model achieves up to 93.86% accuracy on complex system‐cell‐gene association predictions, outperforming the baseline by up to 27.59%.
Boyang Wang, Boyu Pan, Tingyu Zhang, Qingyuan Liu, Shao Li   +4 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

Aging as a Loss of Goal‐Directedness: An Evolutionary Simulation and Analysis Unifying Regeneration with Anatomical Rejuvenation

Advanced Science, EarlyView.
The paper proposes that the root cause of aging is the loss of anatomical goal‐directedness after development. Using evolutionary neural cellular automata simulations, the authors show that after the organism has reached its developmental homeostatic setpoint (the adult morphology), the absence of target state to pursue leads to a drifting anatomical ...
Léo Pio‐Lopez, Benedikt Hartl, Michael Levin   +2 more
wiley   +1 more source

High‐Throughput Strategies for Streamlining Lipid Nanoparticle Development Pipeline

Advanced Science, EarlyView.
This review highlights emerging state‐of‐the‐art high‐throughput strategies for optimising lipid nanoparticle formulation. By integrating combinatorial design, characterization, in vitro/in vivo screening, automation, and machine learning into a closed‐loop framework, it provides a roadmap to streamline discovery and accelerate the translation of ...
Lois Lam, Stephanie Watson, Yogambha Ramaswamy, Gurvinder Singh   +3 more
wiley   +1 more source

Generative Adversarial Networks and Other Generative Models

, 2023
AbstractGenerative networks are fundamentally different in their aim and methods compared to CNNs for classification, segmentation, or object detection. They have initially been meant not to be an image analysis tool but to produce naturally looking images.
openaire   +2 more sources

A Cost‐Effective and Scalable Machine Learning Approach for Quality Assessment of Fresh Maize Kernel Using NIR Spectroscopy

Advanced Science, EarlyView.
A cost‐effective and scalable PCNN approach is developed for NIR model construction that has compatibility with multiple instruments and multiple crops. It is time and cost saving, rapid and nondestructive, small sample set based, various quality properties and extensible for breeding application in fresh maize, forage maize, rice, wheat, and barley ...
Jiang Shi, Erkui Yue, Xuejin Zhu, Lin Zhao, Weifeng Chen, Xiangqun Yu, Hongliang Huang, Ying Qian, Zhengfang Zhang, Jianguo Wu   +9 more
wiley   +1 more source

Towards Virtual H&E Staining of Hyperspectral Lung Histology Images Using Conditional Generative Adversarial Networks [PDF]

, 2017
Neslihan Bayramog̃lu, Mika Kaakinen, Lauri Eklund, Janne Heikkilä   +3 more
openalex   +1 more source

SpaBalance: Balanced Learning for Efficient Spatial Multi‐Omics Decoding

Advanced Science, EarlyView.
SpaBalance is a computational framework that harmonizes multi‐omics learning via gradient equilibrium and dual‐stream feature decomposition, achieving superior clustering accuracy, biological interpretability, and scalable integration of three or more spatial omics modalities.
Yingbo Cui, Yong Zhao, Canqun Yang, Tao Tang, Xiangke Liao, Hongyu Zhang, Huiying Zhao, Zheng Wang, Yuansong Zeng   +8 more
wiley   +1 more source

Advances in generative adversarial network

Tongxin xuebao, 2018
Generative adversarial network (GAN) have swiftly become the focus of considerable research in generative models soon after its emergence,whose academic research and industry applications have yielded a stream of further progress along with the ...
Wanliang WANG, Zhuorong LI
doaj   +2 more sources