Results 161 to 170 of about 203,239 (310)

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Advanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo, Ying Yang, Zizhen Fu, Fengqi Liu, Susu Fang, Kele Xu, Shanshan Wang   +6 more
wiley   +1 more source

Structured learning via convolutional neural networks for vehicle detection

, 2017
One of the main tasks in a vision-based traffic monitoring system is the detection of vehicles. Recently, deep neural networks have been successfully applied to this end, outperforming previous approaches.
Ana I. Maqueda, García Santos, Narciso, Jaureguizar Núñez, Fernando, Carlos R. del Blanco, Fernando Jaureguizar, Maqueda Nieto, Ana Isabel, Blanco Adán, Carlos Roberto del, Narciso García   +7 more
core   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Gradient-Based Pooling for Convolutional Neural Networks

, 2019
Pooling layers are an important part of convolutional neural networks (CNNs). They reduce the dimensionality of feature maps and pass salient information to subsequent layers. In this paper, we introduce a novel gradient-based feature pooling method that
Gao, Y, Jun Zhou, Mohammad Nikzad, Nikzad, M, Zhou, J, Yongsheng Gao   +5 more
core   +1 more source

Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES

Advanced Science, EarlyView.
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu, Wanpeng Zou, Yuekai Li, Jiayi Wang, Mingxuan Cai, Hongmin Cai   +5 more
wiley   +1 more source

Learning temporal information for brain-computer interface using convolutional neural networks

, 2018
Deep learning (DL) methods and architectures have been the state-of-the-art classification algorithms for computer vision and natural language processing problems.
Sakhavi, Siavash, Yan, Shuicheng, Cuntai Guan, Shuicheng Yan, Guan, Cuntai, Siavash Sakhavi   +5 more
core   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Polarization‐Enabled Piezoelectric Tellurium–Selenium (TexSe1–x) Thin Films for Memory Switching and Artificial Synaptic Functions

Advanced Science, EarlyView.
Here, we demonstrate and investigate polarization‐enabled electromechanical responses in cryogenic physical vapor deposition (cryogenic PVD)‐deposited TexSe1‐x thin films, a tellurium‐based compound with a tunable bandgap and enhanced non‐centrosymmetry.
Chia‐Chen Chung, Mayur Chaudhary, Chia‐Hung Lo, Po‐Chien Lai, You‐Jie Lin, Ruei‐Hong Cyu, Yu‐Ren Peng, Bing‐Ni Gu, Zhao‐Feng Lou, Quynh Thi Le, Yi‐Jen Yu, Yen‐Fu Lin, Min‐Hung Lee, Ying‐Hao Chu, Chang‐Hong Shen, Der‐Hsien Lien, Yu‐Lun Chueh   +16 more
wiley   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

Advanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu, Longfei Lv, Fan Zhang, Si Zhou, Weiwei Gao, Jijun Zhao   +5 more
wiley   +1 more source