Results 101 to 110 of about 30,915 (267)
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
mid-DeepLabv3+: A Novel Approach for Image Semantic Segmentation Applied to African Food Dietary Assessments. [PDF]
Baban A Erep TR, Chaari L.
europepmc +1 more source
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
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]
Memon MM +4 more
europepmc +1 more source
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
Trustworthy Breast Ultrasound Image Semantic Segmentation Based on Fuzzy Uncertainty Reduction. [PDF]
Huang K, Zhang Y, Cheng HD, Xing P.
europepmc +1 more source
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 Underwater Garbage with Modified U-Net Architecture Model. [PDF]
Wei L, Kong S, Wu Y, Yu J.
europepmc +1 more source
Image semantic segmentation of indoor scenes: A survey
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

