Results 101 to 110 of about 30,915 (267)

Machine Learning for Designing Perovskites and Perovskite‐Inspired Solar Materials: Emerging Opportunities and Challenges

open access: yesAdvanced Science, EarlyView.
This review offers a comprehensive comparison between perovskites and perovskite‐inspired materials (PIMs), focusing on their crystal structures, electronic properties, and chemical compositions. It evaluates the applicability of machine learning (ML) descriptors and models across both material classes.
Yangfan Zhang   +6 more
wiley   +1 more source

Disentangling the relationships between denomination of origin regulatory councils activities and Spanish wineries' export performance

open access: yesAgribusiness, EarlyView.
Abstract World markets for quality differentiated agri‐food products are highly competitive, presenting significant challenges for firms aiming to compete effectively. Government agencies and business organizations often implement various export promotion policies to address these challenges.
Nicolás Depetris‐Chauvin   +1 more
wiley   +1 more source

Creating Shared Value as an Antecedent of Value Co‐Creation: B2B Relationships in the Agri‐Food Sector

open access: yesAgribusiness, EarlyView.
ABSTRACT This study analyzes the effects of value co‐creation and creation of shared value in agricultural input marketing. This study used a sample of 178 agricultural companies in Costa Rica. The data were analyzed using partial least squares structural equation modeling (PLS‐SEM) with SMART PLS software. Our findings reveal the significant influence
Luis Ricardo Solís‐Rivera   +1 more
wiley   +1 more source

Unified DeepLabV3+ for Semi-Dark Image Semantic Segmentation. [PDF]

open access: yesSensors (Basel), 2022
Memon MM   +4 more
europepmc   +1 more source

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

open access: yesAdvanced 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

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

open access: yesAdvanced 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   +12 more
wiley   +1 more source

Image semantic segmentation of indoor scenes: A survey

open access: yesComputer Vision and Image Understanding
This survey provides a comprehensive evaluation of various deep learning-based segmentation architectures. It covers a wide range of models, from traditional ones like FCN and PSPNet to more modern approaches like SegFormer and FAN. In addition to assessing the methods in terms of segmentation accuracy, we propose to also evaluate the methods in terms ...
Ronny Velastegui   +3 more
openaire   +1 more source

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