Results 61 to 70 of about 203,239 (310)
Doubly Convolutional Neural Networks
CoRR, 2016 Building large models with parameter sharing accounts for most of the success of deep convolutional neural networks (CNNs). In this paper, we propose doubly convolutional neural networks (DCNNs), which significantly improve the performance of CNNs by further exploring this idea.
Shuangfei Zhai +3 more
openaire +3 more sources
Symplectic convolutional neural networks
CoRRWe propose a new symplectic convolutional neural network (CNN) architecture by leveraging symplectic neural networks, proper symplectic decomposition, and tensor techniques. Specifically, we first introduce a mathematically equivalent form of the convolution layer and then, using symplectic neural networks, we demonstrate a way to parameterize the ...
Yildiz, S. +2 more
openaire +3 more sources
Irregular Convolutional Neural Networks [PDF]
2017 4th IAPR Asian Conference on Pattern Recognition (ACPR), 2017 7 pages, 5 figures, 3 ...
Jiabin Ma +2 more
openaire +2 more sources
An exact mapping from ReLU networks to spiking neural networks
, 2023 Deep spiking neural networks (SNNs) offer the promise of low-power artificial intelligence. However, training deep SNNs from scratch or converting deep artificial neural networks to SNNs without loss of performance has been a challenge.
Wulfram Gerstner +11 more
core +1 more source
Clickbait Convolutional Neural Network [PDF]
Symmetry, 2018 With the development of online advertisements, clickbait spread wider and wider. Clickbait dissatisfies users because the article content does not match their expectation. Thus, clickbait detection has attracted more and more attention recently. Traditional clickbait-detection methods rely on heavy feature engineering and fail to distinguish clickbait ...
Hai-Tao Zheng 0002 +5 more
openaire +1 more source
Arthritis Care &Research, EarlyView.Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source
Empowering convolutional networks for malware classification and analysis
, 2022 S.3838-3845Performing large-scale malware classification is increasingly becoming a critical step in malware analytics as the number and variety of malware samples is rapidly growing.
Eraisha, G. +4 more
core +1 more source
Advanced Engineering Materials, EarlyView.This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky +5 more
wiley +1 more source
Clustering-oriented Multiple Convolutional Neural Networks for Single Image Super-resolution [PDF]
, 2017 This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record.In contrast to the human visual system (HVS) that applies different processing schemes to visual information of different textural ...
Ren, Peng +11 more
core +1 more source
Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying
Advanced Engineering Materials, EarlyView.An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara +8 more
wiley +1 more source