Results 131 to 140 of about 41,045 (213)

Temperature‐Tunable Cholesteric Liquid Crystal Optical Combiners for Extended Reality Applications

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Recent advancements in extended reality highlight their potential to enhance traditional displays like liquid crystal displays and organic light‐emitting diode screens. This article introduces an innovative cholesteric liquid crystal‐based optical combiner for head‐mounted displays, enabling seamless transitions between augmented reality, virtual ...
Yuanjie Xia, Haobo Li, Marija Vaskeviciute, Daniele Faccio, Affar S. Karimullah, Hadi Heidari, Rami Ghannam   +6 more
wiley   +1 more source

A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni, Md. Alif Sheakh, Mst. Sazia Tahosin, Md. Zahid Hasan, Taslima Ferdaus Shuva, Touhid Bhuiyan, Muhammad Ali Abdullah Almoyad, Nabil Anan Orka, Md. Tanvir Rahman, Risala Tasin Khan, M. Shamim Kaiser, Mohammad Ali Moni   +11 more
wiley   +1 more source

Accurate and Anti‐Interference Control of Computer Vision‐Assisted Light‐Driven Liquid Crystal Elastomer Actuator

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article introduces a computer vision‐assisted control strategy for light‐driven liquid crystal elastomer actuators. Through negative feedback regulation, the liquid crystal elastomer actuator exhibits accurate and stable bending deformation in complex environments.
Wei Zhang, Zongxuan Wu, Li Lin, Yanjun Liu, Xiaoying Tang, Yajing Shen, Dan Luo   +6 more
wiley   +1 more source

A Memristor‐Based In‐Memory Computing System‐on‐Chip with Efficient Depthwise Convolution

Advanced Intelligent Systems, EarlyView.
We present a memristor‐based in‐memory computing (IMC) architecture that enables efficient depthwise convolution (DWC) acceleration. Fabricated in a system‐on‐chip with crossbar arrays, the design improves memory utilization. Experimental validation demonstrates the first hardware acceleration of DWC in IMC, achieving a digital comparable inference ...
Wenhao Song, Fuxi Cai, Sangsu Park, Zhaoyan Li, Seonghun Lee, Mingyi Rao, Woohyung Choi, Seungin Shin, Yan Zhu, Sujin Chae, Myoungsub Kim, Mingche Wu, Hyejung Choi, Yuan Dao, Jaeyun Yi, Youngman Cho, Seon Yong Cha, Ning Ge, Qiangfei Xia, Soo Gil Kim, Miao Hu, J. Joshua Yang   +21 more
wiley   +1 more source

Scene‐Customized Learning for Multi‐Depth 3D Phase‐Only Hologram Generation

Advanced Intelligent Systems, EarlyView.
 Scene‐customized geometric modeling constructs GM‐4K, a controllable 4K RGB‐D dataset for learning‐based multi‐depth hologram generation. By tuning intensity spectra and depth‐region sampling, the dataset reveals how training‐data statistics affect phase‐only hologram encoding and supports a spectral test framework for evaluating model generalization ...
Yanan Zhang, Jiaqi Li, Tao Jing, Yang Yu, Yang Zhang, Xingpeng Yan   +5 more
wiley   +1 more source

Toward Complex In‐Car Environment Human–Vehicle Interactions Through Smart Glasses and sEMG‐Based Gesture Recognition

Advanced Intelligent Systems, EarlyView.
This study proposes a novel weighted random forest multimodal fusion method that combines smart glasses and sEMG data for in‐vehicle gesture interaction. It realizes stable performance in dim, occluded, and other constrained scenarios, providing feasible solutions and laying a foundation for universal human–machine interaction.
Wenbo Zhang, Wenting Wei, Kuang Li, Chuyuan Bian, Junkai Xu, Jianing Qiu, Yuxi Lu, Bin He, Shuo Jiang   +8 more
wiley   +1 more source

An Intelligent Microfluidics Enabled by Data‐Driven Deep Learning‐Based Microrobot‐Assisted Flow Manipulation

Advanced Intelligent Systems, EarlyView.
An AI‐enabled micromixing framework is developed by integrating cGAN with Bayesian optimization for predictive control of microrobot‐driven flow manipulation. Through this framework, the spatiotemporal evolution of micromixing is learned directly from experimental images, while rapid identification of optimized microrobot actuation strategies is ...
Dineshkumar Loganathan, Chia‐Yuan Chen
wiley   +1 more source

Tailoring Photochromism Beyond Human Eye Visibility: On/Off Switchable NIR Absorption in an Aluminosilicate

Angewandte Chemie, EarlyView.
A new photochromic material was developed. Its on/off‐switchable absorption band is situated completely outside the human eye's visibility, in the near‐infrared (NIR) region, a feature never reported before. The photochromism mechanism in this aluminosilicate is elucidated by combining experimental as well as computational results, and the material's ...
Bettiina Muurinen, Hannah Byron, Teppo Kreivilä, Roosa Vastamäki, Sami Vuori, Tomasz Galica, Ian P. Machado, Sari Granroth, Basit Ali, Maarit Karppinen, Ivo Heinmaa, Milica Todorović, Raphael Rullan, Stephan Steinmann, Tangui Le Bahers, Mika Lastusaari   +15 more
wiley   +2 more sources

Assessment of In Vitro Nano‐Cytotoxicity Through Fluorescence Microscopy via Neural Network‐Based Live/Dead Cell Classification

Advanced Intelligent Systems, EarlyView.
FluoAI is a two‐stage, label‐free method for quantifying nanomaterial‐induced cytotoxicity from conventional fluorescence microscopy images. Mask R‐CNN segmentation and DenseNet‐121 classification provide rapid live/dead classification matching human accuracy.
Ugur C. Topkiran, Ali Gasimli, Lal Durmaz, Diya Vashani, Himish Paul, Giridhar R. Akkaraju, Anton V. Naumov   +6 more
wiley   +1 more source

Designing Wire Mazes for Replicating Natural Echoes to Study Bat Biosonar Function

Advanced Intelligent Systems, EarlyView.
A validated framework combining efficient physical modeling (multiple scattering model) and deep learning is presented to guide wire‐maze design for bat biosonar studies. This approach rapidly generates large datasets to test acoustic distinguishability among wire arrangements.
Chunlin Jia, Gengkai Hu, Boo Cheong Khoo, Rolf Müller   +3 more
wiley   +1 more source