Results 121 to 130 of about 3,030,305 (350)

SCRM-Net: Self-Supervised Deep Clustering Feature Representation for Urban 3D Mesh Semantic Segmentation

Remote Sensing
Semantic urban 3D meshes obtained by deep learning networks have been widely applied in urban analytics. Typically, a large amount of labeled samples are required to train a deep learning network to extract discriminative features for the semantic ...
Jiahui Wang, Wei Leng, Xinjie Hao, Rongting Zhang, Guangyun Zhang   +4 more
doaj   +1 more source

AI‐Enhanced Surface‐Enhanced Raman Scattering for Accurate and Sensitive Biomedical Sensing

Advanced Intelligent Discovery, EarlyView.
AI‐SERS advances spectral interpretation with greater precision and speed, enhancing molecular detection, biomedical analysis, and imaging. This review explores its essential contributions to biofluid analysis, disease identification, therapeutic agent evaluation, and high‐resolution biomedical imaging, aiding diagnostic decision‐making.
Seungki Lee, Rowoon Park, Ho Sang Jung
wiley   +1 more source

Semantic middleware for industrial sensors

Ciência da Informação, 2017
For many years, plant engineers have used data collected from industrial sensors for supporting the diagnosis of failures. Recently, data scientists are using these data to make predictions on industrial processes.
Fernando Silva Parreiras, Vitor Afonso Pinto, Marco Antônio Calijorne Soares, Daniel Henrique Mourão Falci   +3 more
doaj  

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Ontology Alignment—A Survey with Focus on Visually Supported Semi-Automatic Techniques

Future Internet, 2010
Semantic technologies are of paramount importance to the future Internet. The reuse and integration of semantically described resources, such as data or services, necessitates the bringing of ontologies into mutual agreement.
Klaus Tochtermann, Dickson Lukose, Kow Weng Onn, Michael Granitzer, Vedran Sabol   +4 more
doaj   +1 more source

‘Normal’ semantic–phonemic fluency discrepancy in Alzheimer's disease? A meta-analytic study [PDF]

, 2009
Keith R. Laws, Amy Duncan, Tim M. Gale
openalex   +1 more source

Event Search and Analytics [PDF]

Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016
Extended research report of an extended abstract published at WSDM 2016 Doctoral Consortium.
openaire   +5 more sources

Named Entity Recognition Models for Machine Learning Interatomic Potentials: A User‐Centric Approach to Knowledge Extraction from Scientific Literature

Advanced Intelligent Discovery, EarlyView.
Named entity recognition pipeline for knowledge extraction from scientific literature. Machine learning interatomic potential (MLIP) is an emerging technique that has helped achieve molecular dynamics simulations with unprecedented balance between efficiency and accuracy. Recently, the body of MLIP literature has been growing rapidly, which propels the
Bowen Zheng, Grace X. Gu
wiley   +1 more source

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

The Necessity of Dynamic Workflow Managers for Advancing Self‐Driving Labs and Optimizers

Advanced Intelligent Discovery, EarlyView.
We assess the maturity and integration readiness of key methodologies for Materials Acceleration Platforms, highlighting the need for dynamic workflow managers. Demonstrating this, we integrate PerQueue into a color‐mixing robot, showing how flexible orchestration improves coordination and optimization.
Simon K. Steensen, Patrick W. V. Butler, Jesper R. Pedersen, Nis Fisker‐Bødker, Tejs Vegge, Jin Hyun Chang, Ivano E. Castelli   +6 more
wiley   +1 more source