Results 111 to 120 of about 3,700 (260)

Materials Representation Learning Based on a Material–Motif Network and Heterogeneous Graphs

Advanced Intelligent Discovery, EarlyView.
Structure motifs in materials are used to construct a bipartite material–motif network that links each material to its constituent motifs and establishes connectivity among materials sharing common motifs. Network analysis reveals material clusters associated with different functional applications and supports motif‐guided screening of materials.
Anoj Aryal, Weiyi Gong, Huta Banjade, Qimin Yan   +3 more
wiley   +1 more source

Investigation of Analog Memristor Characteristics for Hardware Synaptic Weight in Multilayer Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The systematic design of memristor‐based neural network is provided by analog conductance state parameters to accurately emulate the software‐based high‐resolution weight at discrete device level. The requirement of discrete analog conductance of memristor device is measured as ≈50 states with nonlinearity value of ≈0.142 within the deviation range of ...
Jingon Jang, Yoonseok Song, Sungjun Park
wiley   +1 more source

BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models

Advanced Intelligent Systems, EarlyView.
This study presents a bioinspired metaverse point cloud quality assessment metric, which simulates the human visual evaluation process to perform the point cloud quality assessment task. It first extracts rendering projection video features, normal image features, and point cloud patch features, which are then fed into a large multimodal model to ...
Huiyu Duan, Kang Fu, Sijing Wu, Yunhao Li, Zicheng Zhang, Qiang Hu, Xiongkuo Min, Guangtao Zhai   +7 more
wiley   +1 more source

Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining

Advanced Intelligent Systems, EarlyView.
Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson, Nebojša Maleševic, Anders Björkman, Christian Antfolk   +3 more
wiley   +1 more source

Zero Watermarking Using Convolutional Additive Self‐Attention Vision Transformer and Discrete Wavelet Transform‐Variance‐Based Feature Descriptor for Medical Image Security in Mobile Healthcare Services

Advanced Intelligent Systems, EarlyView.
A zero‐watermarking algorithm that combines a refined convolutional additive self‐attention vision transformer (CAS‐ViT) with a discrete wavelet transform variance‐based feature descriptor (DVFD) is proposed for protecting the privacy of medical images in mobile healthcare services.
Pei Liu, Yan Yan, Hao Huang, Ping Wang, Weirong Qin, Xiangjian Zuo, Yongqin Li   +6 more
wiley   +1 more source

Adaptive Autonomy in Microrobot Motion Control via Deep Reinforcement Learning and Path Planning Synergy

Advanced Intelligent Systems, EarlyView.
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi, Bairong Zhu, Haoyu Liu, Tingting Yu   +3 more
wiley   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

SCP‐Pose: Leveraging Structural Consistency Prior Knowledge for Real‐Time Category‐Level 6D Pose Estimation

Advanced Intelligent Systems, EarlyView.
This paper presents a high‐speed object pose estimation method that deconstructs objects into geometric components. Inspired by human cognitive generalization, it detects these primitives and infers the 6D pose from their stable spatial configuration.
Xuyang Li, Mingxuan Yu, Xuemei Xie, Zhaozhuo An, Qiyue Li, Xiaodan Song, Guangming Shi   +6 more
wiley   +1 more source

Resource‐Aware Contrastive Scattering Meta‐Learning for Efficient Few‐Shot Acoustic Anomaly Detection

Advanced Intelligent Systems, EarlyView.
This paper introduces a resource‐aware Contrastive Scattering Meta‐Learning (CSML) framework for acoustic anomaly detection. By leveraging training‐free wavelet scattering and metric‐based meta‐learning, the model achieves competitive performance with only 50 K learnable parameters—a 98% reduction compared to state‐of‐the‐art frameworks—enabling ...
Rami Zewail, Bassem Mokhtar
wiley   +1 more source

Thermally Stable Organic Synaptic Transistors Using a High‐Tg Polymer Electret

Advanced Intelligent Systems, EarlyView.
A high–glass‐transition‐temperature cyclic olefin copolymer (COC) electret enables thermally stable organic synaptic transistors for neuromorphic operation in harsh environments. UV–ozone treatment increases the trap density in COC, providing robust multilevel conductance and key synaptic functions (excitatory postsynaptic current/ inhibitory ...
Hoyoung Cho, Bombi Kim, Kyoungeun Lee, Moohyun Kim, Chaegwang Lim, Yeyun Bae, Jaeyeop Lee, Jiyoon Oh, Hyeok Kim, Jeongkyun Roh   +9 more
wiley   +1 more source