Results 51 to 60 of about 9,200 (172)

Advancing the Reliability of Future Hydrological Projections in a Snow‐Dominated Alpine Watershed: Integrating Uncertainty Decomposition and CycleGAN Bias Correction

Earth's Future
Given the sensitivity of snow to climate change and its critical role in the hydrological cycle of alpine regions, it is essential to reduce biases in meteorological forces for driving hydrological models.
Tao Su, Zhu Liu, Qingyun Duan, Xinwei Mao, Weidong Xu   +4 more
doaj   +1 more source

Low illumination image enhancement algorithm of CycleGAN coal mine based on attention mechanism and Dilated convolution

Meitan kexue jishu
The complex underground environment, filled with a large amount of dust and water vapor, and uneven illumination of artificial light source, leads to problems such as low illumination and loss of detail features in images collected by underground ...
Yuanbin WANG, Yaru GUO, Jia LIU, Xu WANG, Bingchao WU, Meng LIU   +5 more
doaj   +1 more source

Robust Dysarthric Speech Recognition with GAN Enhancement and LLM Correction

Advanced Intelligent Systems, EarlyView.
This study tackles dysarthric speech recognition by combining generative adversarial network (GAN)‐generated synthetic data with large language model (LLM)‐based error correction. The approach integrates three key elements: an improved CycleGAN to generate synthetic dysarthric speech for data augmentation, a multimodal automatic speech recognition core
Yibo He, Kah Phooi Seng, Chee Shen Lim, Li Minn Ang   +3 more
wiley   +1 more source

High-Quality Facial Photo-Sketch Synthesis Using Multi-Adversarial Networks

, 2018
Synthesizing face sketches from real photos and its inverse have many applications. However, photo/sketch synthesis remains a challenging problem due to the fact that photo and sketch have different characteristics. In this work, we consider this task as
Patel, Vishal M., Sindagi, Vishwanath A., Wang, Lidan   +2 more
core   +1 more source

Detail-Preserving CycleGAN-AdaIN Framework for Image-to-Ink Painting Translation

IEEE Access, 2020
Image translation tasks based on generative models have become an important research area, such as the general framework for unsupervised image translation-CycleGAN (Cycle-Consistent Generative Adversarial Networks).
Fengquan Zhang, Huaming Gao, Yuping Lai
doaj   +1 more source

Generating Diffusion MRI scalar maps from T1 weighted images using generative adversarial networks

, 2019
Diffusion magnetic resonance imaging (diffusion MRI) is a non-invasive microstructure assessment technique. Scalar measures, such as FA (fractional anisotropy) and MD (mean diffusivity), quantifying micro-structural tissue properties can be obtained ...
DC Essen Van, Dong Nie, E Özarslan, H Emami, Jelmer M. Wolterink, MF Glasser, Sahin Olut, Z Wang   +7 more
core   +1 more source

Deep Learning Integration in Optical Microscopy: Advancements and Applications

Microscopy Research and Technique, EarlyView.
It explores the integration of DL into optical microscopy, focusing on key applications including image classification, segmentation, and computational reconstruction. ABSTRACT Optical microscopy is a cornerstone imaging technique in biomedical research, enabling visualization of subcellular structures beyond the resolution limit of the human eye ...
Pottumarthy Venkata Lahari, Sagnika Dutta, H. Deeksha, Samreen A. Patel, Budheswar Dehury, Nirmal Mazumder   +5 more
wiley   +1 more source

Graded Image Generation Using Stratified CycleGAN

, 2020
In medical imaging, CycleGAN has been used for various image generation tasks, including image synthesis, image denoising, and data augmentation. However, when pushing the technical limits of medical imaging, there can be a substantial variation in image quality.
Jianfei, Liu, Joanne, Li, Tao, Liu, Johnny, Tam   +3 more
openaire   +3 more sources

Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang, Daeun Choi, Damian Adams, Jaehyun Ahn, Kelly Balmant, Raquel Dias, Carlos D. Messina, Rafael Muñoz‐Carpena, Vance M. Whitaker, Haipeng Yu, Ziwen Yu, Chang Zhao, Changying Li   +12 more
wiley   +1 more source

Rapid Arbitrary‐Shape Microscopy of Unsectioned Tissues for Precise Intraoperative Tumor Margin Assessment

Advanced Science, Volume 13, Issue 8, 9 February 2026.
This study presents a novel microscopic imaging system capable of rapid, section‐free scanning of irregular tissue surfaces, delivering high sensitivity for detecting cancer cell clusters during intraoperative tumor margin assessment. Abstract Rapid and accurate intraoperative examination of tumor margins is crucial for precise surgical treatment, yet ...
Zhicheng Shao, Xiangwei Meng, Peifen Fu, Keer Huang, Xibei Chen, Yue Ying, Jun Li, Yuxin Zheng, Xiaolong Li, Hyeon Jeong Lee, Jingyi Feng, Yuexin Lu, Runping Cai, Xiongling Jiang, Qing Chen, Hong Zhang, Xiaoyong Man, Li Lin   +17 more
wiley   +1 more source