Results 71 to 80 of about 199,179 (229)

Machine Learning for Organic Fluorescent Materials

Aggregate, EarlyView.
Organic fluorescent materials (OFMs) have demonstrated significant potential in diverse applications. Conventional approaches for studying OFMs face significant limitations in fluorescence spectroscopy and computational methods. Machine learning (ML) has revolutionized materials chemistry, offering superior predictive accuracy and efficiency over ...
Jiamin Zhong, Wei Zhu, Shoutao Shen, Nan Zhou, Meiyang Xi, Kui Du, Dong Wang, Ben Zhong Tang   +7 more
wiley   +1 more source

On minimizing the number of ADMs in a general topology optical network

Discrete Applied Mathematics, 2006
M. Flammini, Mordechai Shalom, S. Zaks
semanticscholar   +1 more source

In Situ Graph Reasoning and Knowledge Expansion Using Graph‐PRefLexOR

Advanced Intelligent Discovery, EarlyView.
Graph‐PRefLexOR is a novel framework that enhances language models with in situ graph reasoning, symbolic abstraction, and recursive refinement. By integrating graph‐based representations into generative tasks, the approach enables interpretable, multistep reasoning.
Markus J. Buehler
wiley   +1 more source

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

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Widened Attention‐Enhanced Atrous Convolutional Network for Efficient Embedded Vision Applications under Resource Constraints

Advanced Intelligent Systems, EarlyView.
The article introduces WACEfNet, a new convolutional neural network architecture optimized for efficient aerial image analysis under resource constraints. It creatively integrates attention mechanisms and atrous convolutions into a compact widened residual network framework.
Md Meftahul Ferdaus, Mahdi Abdelguerfi, Kendall N. Niles, Ken Pathak, Joe Tom   +4 more
wiley   +1 more source

Advancements in Machine Learning for Microrobotics in Biomedicine

Advanced Intelligent Systems, EarlyView.
Microrobotics is an innovative technology with great potential for noninvasive medical interventions. However, controlling and imaging microrobots pose significant challenges in complex environments and in living organisms. This review explores how machine learning algorithms can address these issues, offering solutions for adaptive motion control and ...
Amar Salehi, Soleiman Hosseinpour, Nasrollah Tabatabaei, Mahmoud Soltani Firouz, Niloufar Zadebana, Richard Nauber, Mariana Medina‐Sánchez   +6 more
wiley   +1 more source

Uncontrolled Learning: Codesign of Neuromorphic Hardware Topology for Neuromorphic Algorithms

Advanced Intelligent Systems, EarlyView.
Codesign is used to implement a neuroscience‐inspired machine learning algorithm in all neuromorphic hardware. In this implementation, the hidden memristors cannot be directly accessed, limiting control of the network during training. By leveraging theoretical tools, including memristor circuits dynamics and a closed form expression for the network ...
Frank Barrows, Jonathan Lin, Francesco Caravelli, Dante R. Chialvo   +3 more
wiley   +1 more source

Applied Artificial Intelligence in Materials Science and Material Design

Advanced Intelligent Systems, EarlyView.
AI‐driven methods are transforming materials science by accelerating material discovery, design, and analysis, leveraging large datasets to enhance predictive modeling and streamline experimental techniques. This review highlights advancements in AI applications across spectroscopy, microscopy, and molecular design, enabling efficient material ...
Emigdio Chávez‐Angel, Martin Børstad Eriksen, Alejandro Castro‐Alvarez, Jose H. Garcia, Marc Botifoll, Oscar Avalos‐Ovando, Jordi Arbiol, Aitor Mugarza   +7 more
wiley   +1 more source

Mainstream Artificial Intelligence Technologies in Contemporary Ophthalmology

Advanced Intelligent Systems, EarlyView.
This review explores the latest artificial intelligence (AI) technologies in ophthalmology, focusing on four key data types: medical imaging, electronic health records, robotic‐assisted surgery, and genomics. It examines the structural features, use cases, clinical goals, and evaluation metrics of various AI algorithms, while also introducing emerging ...
Shiqi Yin, Lei Wang, Shanjun Wu, Jiewei Jiang, Wei Qiang, Yangyang Wang, Shihong Wang, Yi Shao, Wei Chen, Zhongwen Li   +9 more
wiley   +1 more source