Results 51 to 60 of about 505,774 (261)

Amyloidogenic Peptide Fragments Designed From Bacterial Collagen‐like Proteins Form Hydrogel

Advanced Functional Materials, EarlyView.
This study identified amyloidogenic sequence motifs in bacterial collagen‐like proteins and exploited these to design peptides that self‐assemble into β‐sheet fibers and form hydrogels. One hydrogel supported healthy fibroblast growth, showing promise for biocompatible materials. Our work demonstrates that bacterial sequences can be harnessed to create
Vamika Sagar, Xuen J Ng, Lukas Lechel, Ashish Chand Rajwar, Hendrik Bargel, Abhishek A. Jalan   +5 more
wiley   +1 more source

Review of Node Classification Methods Based on Graph Convolutional Neural Networks [PDF]

Jisuanji kexue
Node classification is one of the important research tasks in graph field.In recent years,with the continuous deepening of research on graph convolutional neural network,significant progress has been made in the research and application of node ...
ZHANG Liying, SUN Haihang, SUN Yufa , SHI Bingbo
doaj   +1 more source

SMT Assembly Inspection Using Dual-Stream Convolutional Networks and Two Solder Regions

Applied Sciences, 2020
The automated optical inspection of a surface mount technology line inspects a printed circuit board for quality assurance, and subsequently classifies the chip assembly defects.
Young-Gyu Kim, Tae-Hyoung Park
doaj   +1 more source

Multi‐Scale Interface Engineering of MXenes for Multifunctional Sensory Systems

Advanced Functional Materials, EarlyView.
MXenes, as two‐dimensional transition metal carbides and nitrides, demonstrate remarkable capabilities for multifunctional sensing applications. This review systematically examines multi‐scale interface engineering approaches that enhance sensing performance, enable diverse detection functionalities, and improve system‐level compatibility in MXene ...
Jiaying Liao, Sin‐Yi Pang, Jianhua Hao
wiley   +1 more source

Orthogonal Features Extraction Method and Its Application in Convolution Neural Network

Shanghai Jiaotong Daxue xuebao, 2021
In view of feature redundancy in the convolutional neural network, the concept of orthogonal vectors is introduced into features. Then, a method for orthogonal features extraction of convolutional neural network is proposed from the perspective of ...
LI Chen, LI Jianxun
doaj   +1 more source

Addressing Item-Cold Start Problem in Recommendation Systems using Model Based Approach and Deep Learning

, 2017
Traditional recommendation systems rely on past usage data in order to generate new recommendations. Those approaches fail to generate sensible recommendations for new users and items into the system due to missing information about their past ...
A Rajaraman, D Stojanovski, F Ricci, G Cormode, R Collobert   +4 more
core   +1 more source

Atomic Layer Deposition in Transistors and Monolithic 3D Integration

Advanced Functional Materials, EarlyView.
Transistors are fundamental building blocks of modern electronics. This review summarizes recent progress in atomic layer deposition (ALD) for the synthesis of two‐dimensional (2D) metal oxides and transition‐metal dichalcogenides (TMDCs), with particular emphasis on their enabling role in monolithic three‐dimensional (M3D) integration for next ...
Yue Liu, Taoyu Zou, Cheng‐Yan Xu, Liang Zhen, Yang Li, Yong‐Young Noh   +5 more
wiley   +1 more source

Forest fire image recognition based on convolutional neural network

Journal of Algorithms & Computational Technology, 2019
In order to detect fire automatically, a forest fire image recognition method based on convolutional neural networks is proposed in this paper. There are two main types of fire recognition algorithms.
Yuanbin Wang, Langfei Dang, Jieying Ren
doaj   +1 more source

Design Strategies and Emerging Applications of High‐Performance Flexible Piezoresistive Pressure Sensors

Advanced Functional Materials, EarlyView.
Flexible piezoresistive pressure sensors underpin wearable and soft electronics. This review links sensing physics, including contact resistance modulation, quantum tunneling and percolation, to unified materials/structure design. We highlight composite and graded architectures, interfacial/porous engineering, and microstructured 3D conductive networks
Feng Luo, Artur Ciesielski, Paolo Samorì   +2 more
wiley   +1 more source

INVESTIGATIONS ON THE POTENTIAL OF CONVOLUTIONAL NEURAL NETWORKS FOR VEHICLE CLASSIFICATION BASED ON RGB AND LIDAR DATA [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017
In recent years, there has been a significant improvement in the detection, identification and classification of objects and images using Convolutional Neural Networks.
R. Niessner, H. Schilling, B. Jutzi
doaj   +1 more source