Results 111 to 120 of about 4,404,768 (300)

Advances in Sustainable and Wearable Textile Based Soft Robotics

Advanced Functional Materials, EarlyView.
This Review examines advances in wearable textile‐based soft robotics, focusing on sustainable materials, integrated sensing, and scalable actuation. It discusses manufacturing and system integration across healthcare, assistive robotics, prosthetics, and human–machine interfaces, and highlights key challenges in circular design, including life‐cycle ...
Zahir Abbas, Marzia Dulal, Sophia K. Novoselov, Victoria K. Novoselov, Kostya S. Novoselov, Shaila Afroj, Nazmul Karim   +6 more
wiley   +1 more source

Zero-Learning Fast Medical Image Fusion [PDF]

Clinical applications, such as image-guided surgery and noninvasive diagnosis, rely heavily on multi-modal images. Medical image fusion plays a central role by integrating information from multiple sources into a single, more understandable output.
Suesstrunk, Sabine, Lahoud, Fayez, Süsstrunk, Sabine   +2 more
core   +1 more source

Optical Signature of Moiré Superlattices Formed by Twisted SrTiO3 Membranes

Advanced Functional Materials, EarlyView.
We discover optical signatures from bonded interfaces in twisted SrTiO3 moiré superlattices, including low‐frequency Raman vibrational modes and strong second‐harmonic generation, consistent with strong interlayer coupling inferred from cross‐sectional electron microscopy and ab initio calculations. ABSTRACT Moiré superlattices formed at the interfaces
T. A. M. Ragib Shahriar, Fumikazu Murakami, Xing He, Konnor Koons, Xinyan Li, Bumseop Kim, Shihan Qin, Varun Harbola, Jochen Mannhart, Yimo Han, Ruijuan Xu, Shengxi Huang, Andrew M. Rappe, Hanyu Zhu   +13 more
wiley   +1 more source

Multi-modal Fusion Technology based on Vehicle Information: A Survey

, 2022
Multi-modal fusion is a basic task of autonomous driving system perception, which has attracted many scholars' interest in recent years. The current multi-modal fusion methods mainly focus on camera data and LiDAR data, but pay little attention to the ...
Gong, Yan, Wu, Jiayi, Lu, Jianli, Liu, Wenzhuo   +3 more
core  

Multi-label remote sensing classification with self-supervised gated multi-modal transformers

Frontiers in Computational Neuroscience
IntroductionWith the great success of Transformers in the field of machine learning, it is also gradually attracting widespread interest in the field of remote sensing (RS).
Na Liu, Ye Yuan, Guodong Wu, Sai Zhang, Jie Leng, Lihong Wan   +5 more
doaj   +1 more source

Electrospun Wood‐Derived Biopolymers as Electrodes in Electrochemical Energy Storage Technologies

Advanced Functional Materials, EarlyView.
Electrospinning transforms wood‐derived cellulose and lignin into architecturally defined, binder‐free carbon electrodes with tuneable porosity and functionality. This review shows how fibre design enables decoupled charge and mass transport, enhancing performance across battery systems, while identifying key challenges in spinnability, scalability ...
Michael W. Thielke, Hattie R. Chisnall, Jesus Vazquez Chavez, Ana B. Jorge Sobrido   +3 more
wiley   +1 more source

Missing-modality Enabled Multi-modal Fusion Architecture for Medical Data

, 2023
Fusing multi-modal data can improve the performance of deep learning models. However, missing modalities are common for medical data due to patients' specificity, which is detrimental to the performance of multi-modal models in applications.
Li, Yichen, Chen, Hui, Wang, Muyu, Fan, Shiyu   +3 more
core  

Fusogenic RNA Nanomodules for Fusion‐Mediated and Multiplexed siRNA Delivery

Advanced Functional Materials, EarlyView.
A fusogenic lipid‐layered RNA nanomodules (L‐CRAMs) enable high‐capacity and long‐lasting siRNA delivery through membrane fusion. These nanomodules carry exceptionally large siRNA payloads, avoid conventional endosomal uptake, and release multiple functional siRNAs through Dicer‐mediated processing.
Sunghyun Moon, Iksoo Jang, Taehyeon Kim, Nayoung Yoon, Kyuha Yum, Jong Bum Lee   +5 more
wiley   +1 more source

A Generalized Multi-Modal Fusion Detection Framework [PDF]

LiDAR point clouds have become the most common data source in autonomous driving. However, due to the sparsity of point clouds, accurate and reliable detection cannot be achieved in specific scenarios.
Meng, Min, Li, Xiuxian, Cui, Leichao, Mo, Xiaoyu   +3 more
core   +1 more source

Granularity-guided fusion for multi-modal sentiment understanding

Scientific Reports
Abstract Multimodal sarcasm detection involves identifying sarcasm through multiple modalities of information, with the key challenge lying in modeling incongruity within and between modalities. Current methods often focus on intermodal incongruity while neglecting the potential of fully exploring semantic information within each ...
Mingxuan, Chen, Huarong, Tang, Chen, Sun, Nannan, Zhang   +3 more
openaire   +2 more sources