Results 91 to 100 of about 1,429,068 (340)

Cottonseed‐Derived Reusable Bio‐Carbon Gel Ink for DIW Printing Soft Electronic Textiles

Advanced Materials, EarlyView.
A reusable carbon‐gel ink, incorporating cottonseed peptone as a natural mediator, enables cross‐linked ionic polymer networks for advanced conductivity, stability, and biocompatibility. Compatible with direct‐ink‐writing, it facilitates flexible electronics on polymeric and textile substrates for multifunctional applications, including motion sensing,
King Yan Chung, Di Tan, Ziyu He, Xiao Li, Jian Lu, Qingjun Yang, Xinlong Liu, Bingang Xu   +7 more
wiley   +1 more source

Quaternion Convolutional Neural Networks [PDF]

, 2018
Neural networks in the real domain have been studied for a long time and achieved promising results in many vision tasks for recent years. However, the extensions of the neural network models in other number fields and their potential applications are not fully-investigated yet. Focusing on color images, which can be naturally represented as quaternion
Changjian Chen, Hongteng Xu, Yi Xu, Xuanyu Zhu   +3 more
openaire   +3 more sources

Machine‐Learning‐Aided Advanced Electrochemical Biosensors

Advanced Materials, EarlyView.
Electrochemical biosensors are highly sensitive, portable, and versatile. Advanced nanomaterials enhance their performance, while machine learning (ML) improves data analysis, minimizes interference, and optimizes sensor design. Despite progress in both fields, their combined potential in diagnostics remains underexplored.
Andrei Bocan, Roozbeh Siavash Moakhar, Carolina del Real Mata, Max Petkun, Tristan De Iure‐Grimmel, Sripadh Guptha Yedire, Hamed Shieh, Arash Khorrami Jahromi, Sahar Sadat Mahshid, Sara Mahshid   +9 more
wiley   +1 more source

Powerset Convolutional Neural Networks

, 2019
We present a novel class of convolutional neural networks (CNNs) for set functions, i.e., data indexed with the powerset of a finite set. The convolutions are derived as linear, shift-equivariant functions for various notions of shifts on set functions.
Wendler, Chris, Alistarh, Dan-Adrian, Püschel, Markus   +2 more
openaire   +2 more sources

Recurrent Convolutional Neural Networks for Text Classification

AAAI Conference on Artificial Intelligence, 2015
Text classification is a foundational task in many NLP applications. Traditional text classifiers often rely on many human-designed features, such as dictionaries, knowledge bases and special tree kernels.
Siwei Lai, Liheng Xu, Kang Liu, Jun Zhao
semanticscholar   +1 more source

Photonic Nanomaterials for Wearable Health Solutions

Advanced Materials, EarlyView.
This review discusses the fundamentals and applications of photonic nanomaterials in wearable health technologies. It covers light‐matter interactions, synthesis, and functionalization strategies, device assembly, and sensing capabilities. Applications include skin patches and contact lenses for diagnostics and therapy. Future perspectives emphasize AI‐
Taewoong Park, Jung Woo Leem, Young L. Kim, Chi Hwan Lee   +3 more
wiley   +1 more source

AAGCN: a graph convolutional neural network with adaptive feature and topology learning

Scientific Reports
In recent years, there has been a growing prevalence of deep learning in various domains, owing to advancements in information technology and computing power.
Bin Wang, Bodong Cai, Jinfang Sheng, Wenzhe Jiao   +3 more
doaj   +1 more source

An Embedded Inference Framework for Convolutional Neural Network Applications

IEEE Access, 2019
With the rapid development of deep convolutional neural networks, more and more computer vision tasks have been well resolved. These convolutional neural network solutions rely heavily on the performance of the hardware. However, due to privacy issues or
Sheng Bi, Yingjie Zhang, Min Dong, Huaqing Min   +3 more
doaj   +1 more source

Challenges and Opportunities of Upconversion Nanoparticles for Emerging NIR Optoelectronic Devices

Advanced Materials, EarlyView.
The special photo‐responsiveness of upconversion nanoparticles has opened up a new path for the advancement of near‐infrared (NIR)‐responsive optoelectronics. However, challenges such as low energy‐conversion efficiency and high nonradiative losses still persist.
Sunyingyue Geng, Hangfei Li, Ziyu Lv, Yongbiao Zhai, Bobo Tian, Ying Luo, Ye Zhou, Su‐Ting Han   +7 more
wiley   +1 more source

Deep Learning as Applied in SAR Target Recognition and Terrain Classification

Leida xuebao, 2017
Deep learning such as deep neural networks has revolutionized the computer vision area. Deep learning-based algorithms have surpassed conventional algorithms in terms of performance by a significant margin. This paper reviews our works in the application
Xu Feng, Wang Haipeng, Jin Yaqiu
doaj   +1 more source