Results 81 to 90 of about 6,849,681 (296)

HU‐PageScan: a fully convolutional neural network for document page crop

IET Image Processing, 2020
November The offer of online, automated, and impersonal services demand users to upload scanned copies of their documents to the organisations. As a consequence of this decentralisation, the documents present more challenges to the already complex ...
Ricardo Batista dasNeves Junior, Estanislau Lima, Byron L.D. Bezerra, Cleber Zanchettin, Alejandro H. Toselli   +4 more
doaj   +1 more source

Fully Learnable Group Convolution for Acceleration of Deep Neural Networks [PDF]

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Benefitted from its great success on many tasks, deep learning is increasingly used on low-computational-cost devices, e.g. smartphone, embedded devices, etc. To reduce the high computational and memory cost, in this work, we propose a fully learnable group convolution module (FLGC for short) which is quite efficient and can be embedded into any deep ...
Xijun Wang 0002, Meina Kan, Shiguang Shan, Xilin Chen 0001   +3 more
openaire   +3 more sources

Memristor-Based Design of Sparse Compact Convolutional Neural Network

, 2021
© 2013 IEEE. Memristor has been widely studied for hardware implementation of neural networks due to the advantages of nanometer size, low power consumption, fast switching speed and functional similarity to biological synapse.
Huang, T, Wen, S, Yan, Z, Yang, Y, Wei, H, Chen, Y, Guo, Z   +6 more
core   +1 more source

Quantifying Subsurface Weak in‐Plane Magnetization of Mixed Phase BiFeO3 by Scanning Nitrogen Vacancy Magnetometry

Advanced Functional Materials, EarlyView.
We use scanning nitrogen vacancy magnetometry to directly image the weak in‐plane magnetic moments in mixed phase BiFeO3 at the nanoscale and quantify the local magnetic moments to be 18.8±2.0 μB/nm2 in the rhombohedral‐like phase and 1.5±0.6 μB/nm2 in the well‐known non‐magnetic tetragonal‐like phase.
Lei Wang, Zhewen Xu, Yuwen Xu, Björn Josteinsson, Simon Josephy, Dawei Zhang, Yunlong Sun, Heung‐Sik Park, Jihun Kim, Kanghyun Chu, Kyung Song, Danyang Wang, Chan‐Ho Yang, Andrea Morales, Jan Seidel   +14 more
wiley   +1 more source

Modeling of complex-valued Wiener systems using B-spline neural network

, 2011
In this brief, a new complex-valued B-spline neural network is introduced in order to model the complex-valued Wiener system using observational input/output data. The complex-valued nonlinear static function in the Wiener system is represented using the
Hong, Xia, null Sheng Chen, Chen, Sheng, null Xia Hong   +3 more
core   +2 more sources

Recurrent Neural Network Based Narrowband Channel Prediction

, 2006
In this contribution, the application of fully connected recurrent neural networks (FCRNNs) is investigated in the context of narrowband channel prediction.
Liu, W., Yang, L-L., Hanzo, L.
core   +1 more source

Noise‐Limited Bit Precision in Ferroelectric Synaptic Transistors for High‐Resolution Neuromorphic Computing

Advanced Functional Materials, EarlyView.
Low‐frequency noise spectroscopy defines the resolvable conductance states of synaptic FeFETs by coupling read‐current fluctuation with usable dynamic range. The resulting noise‐limited bit precision establishes a universal, device‐agnostic reliability metric beyond the memory window, enabling quantitative benchmarking and rational design of high ...
Jaehong Park, Yeonseop Shin, Changhyeon Han, Sangwoo Kim, Eunchan Park, Youngchan Cho, Jaehong Min, Hyunjun Ahn, Jaekyoung Park, Cheol‐Woong Yang, Jangsaeng Kim, Daewoong Kwon, Wonjun Shin   +12 more
wiley   +1 more source

Reconfigurable Au Nanoparticle Monolayers on Regenerated Cellulose Hydrogels: Highly Sensitive SERS Detection of Polystyrene Micro/Nanoplastics With Interpretable Deep Learning

Advanced Functional Materials, EarlyView.
A regenerated cellulose (RC) hydrogel‐based SERS substrate integrating a Marangoni‐transferred gold nanoparticle self‐assembled monolayer (Au‐SAM) is fabricated. Reswelling‐induced hotspot formation enhances polystyrene micro/nanoplastics (PS MNPs) detection in complex matrices, providing reproducible, high‐throughput SERS signals across diverse ...
Youngho Jeon, Yu‐Jin Jeon, Suji Lee, Jeseong Kim, Dae‐Hyun Jung, Jungmok You   +5 more
wiley   +1 more source

Fully differentiable Lagrangian convolutional neural network for physics-informed precipitation nowcasting

Applied Computing and Geosciences
This paper presents a convolutional neural network model for precipitation nowcasting that combines data-driven learning with physics-informed domain knowledge.
Peter Pavlík, Martin Výboh, Anna Bou Ezzeddine, Viera Rozinajová   +3 more
doaj   +1 more source

P-Wave Detection Using a Fully Convolutional Neural Network in Electrocardiogram Images

Applied Sciences, 2020
Electrocardiogram (ECG) signal analysis is a critical task in diagnosing the presence of any cardiac disorder. There are limited studies on detecting P-waves in various atrial arrhythmias, such as atrial fibrillation (AFIB), atrial flutter, junctional ...
Rana N. Costandy, Safa M. Gasser, Mohamed S. El-Mahallawy, Mohamed W. Fakhr, Samir Y. Marzouk   +4 more
doaj   +1 more source