Results 71 to 80 of about 5,839,842 (237)

Artificial Intelligence in Ophthalmology: From Methodological Advances to Clinical Translation and Future Directions

Eye &ENT Research, EarlyView.
ABSTRACT Artificial intelligence (AI) is reshaping ophthalmology from task‐specific image analysis toward multimodal, longitudinal, and clinically integrated decision support. This narrative review summarizes the methodological evolution of ophthalmic AI, including traditional machine learning, task‐specific deep learning, self‐supervised learning ...
Yuxin Liu, Hanruo Liu
wiley   +1 more source

Semantic segmentation of point clouds of ancient buildings based on weak supervision

Heritage Science
Semantic segmentation of point clouds of ancient buildings plays an important role in Historical Building Information Modelling (HBIM). As the annotation task of point cloud of ancient architecture is characterised by strong professionalism and large ...
Jianghong Zhao, Haiquan Yu, Xinnan Hua, Xin Wang, Jia Yang, Jifu Zhao, Ailin Xu   +6 more
doaj   +1 more source

Citrus Essential Oils in Food Safety and Health: Advances in AI‐Assisted Authentication, Antimicrobial Applications, Sustainable Extraction, and Regulatory Translation

Food Safety and Health, EarlyView.
Citrus essential oils combine sustainable extraction, AI‐assisted authentication, multi‐omics profiling, antimicrobial activity, and regulatory safety to enhance food quality, detect adulteration, and promote consumer health, and support intelligent, sustainable food systems through innovative industrial applications and circular bioeconomy strategies.
Md. Hassan Bin Nabi, Liza Akter, Yusuf Chowdhury, Mohima Akther Any, Nazmul Islam, Erni Sofia Murtini, Nurul Huda, Wahidu Zzaman   +7 more
wiley   +1 more source

A quality-aware cloud selection service for computational modellers [PDF]

, 2012
This research sets out to help computational modellers, to select the most cost effective Cloud service provider. This is when they opt to use Cloud computing in preference to using the in-house High Performance Computing (HPC) facilities.
Nizamani, Shahzad Ahmed
core   +4 more sources

SEMANTIC SEGMENTATION OF BUILDING ELEMENTS USING POINT CLOUD HASHING [PDF]

, 2018
For the interpretation of point clouds, the semantic definition of extracted segments from point clouds or images is a common problem. Usually, the semantic of geometrical pre-segmented point cloud elements are determined using probabilistic networks and
M. Chizhova, A. Gurianov, T. Luhmann, U. Stilla, M. Hess, A. Brunn   +5 more
core   +1 more source

Multi‐omics–driven precision medicine

iMeta, EarlyView.
Multi‐omics‐driven precision medicine (MODPM) provides a multiscale, continuously learnable framework that integrates genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiome profiles, and clinical data. Powered by artificial intelligence and foundation models, MODPM enables cross‐modal representation learning, contextual modeling ...
Huibo Li, Zhe Zhao, Yifan Zhang, Yao Ma, Gaofei Hu, Min Zeng, Zhanqun Yang, Zixuan Zhao, Xin Zhou, Wei Hu, Yuxuan Sun, Meng Su, Jun Li, Matthew Whiteman, Wei Fu, Chao Zhong, Lemin Zheng, Long Chen, Hairong Lv, Rongsheng Zhao, Yi Zhun Zhu   +20 more
wiley   +1 more source

3D Scene Segmentation for Autonomous Robot Grasping [PDF]

, 2012
Ückermann A, Elbrechter C, Haschke R, Ritter H. 3D Scene Segmentation for Autonomous Robot Grasping. Presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012), Algarve, Portugal.We present an algorithm to segment an
Ückermann, André, Elbrechter, Christof, Ritter, Helge ; https://orcid.org/, Haschke, Robert ; https://orcid.org/, Robert Haschke, Andre Uckermann, Helge Ritter, Christof Elbrechter   +7 more
core   +1 more source

SparGlu: A sparse‐data evaluation framework for gated recurrent unit‐based blood glucose prediction across varying monitoring intervals

Journal of Intelligent Medicine, EarlyView.
A sparse‐aware GRU model accurately predicts blood glucose levels using downsampled and limited data, achieving clinically safe forecasts even under low‐monitoring conditions. By effectively capturing glucose dynamics through residual learning, the model supports personalized diabetes self‐management, offering a practical solution for resource‐limited ...
Genet Tadese Aboye, Jasper Gielen, Gizeaddis Lamesgin Simegn, Jean‐Marie Aerts   +3 more
wiley   +1 more source

Point cloud semantic segmentation of grotto scenes using the knowledge-guided deep learning method

International Journal of Digital Earth
In recent years, the deep learning-based semantic segmentation for point clouds has demonstrated remarkable capabilities in processing 3D urban scenes for applications such as three-dimensional reconstruction, semantic modeling, and augmented reality ...
Su Yang, Miaole Hou, Songnian Li
doaj   +1 more source

Revealing Dust Source Changes in East Asia From Past to Future: An Interpretable Deep Learning Approach

Land Degradation &Development, EarlyView.
ABSTRACT Aeolian dust source areas are controlled by climate and human activities and are closely associated with land degradation, yet their long‐term evolution under global warming remains insufficiently quantified. An integrated framework that couples a U‐Net segmentation model with Shapley Additive Explanations (SHAP) was built to map and attribute
Yanyu Li, Qizhong Wu, Xueshun Chen, Jiang Yue, Jieying He, Huaqiong Cheng   +5 more
wiley   +1 more source