Results 21 to 30 of about 54,299 (266)
IEEE Access, 2019 Deep learning is an important support for the development of cognitive communication in the cognitive Internet of Things (IoT). Deep convolution neural networks have powerful functional expression and feature extraction capabilities.
Huaji Zhou +6 more
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Orthogonal Convolutional Neural Networks [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 Deep convolutional neural networks are hindered by training instability and feature redundancy towards further performance improvement. A promising solution is to impose orthogonality on convolutional filters. We develop an efficient approach to impose filter orthogonality on a convolutional layer based on the doubly block-Toeplitz matrix ...
Jiayun Wang +3 more
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AresB-Net: accurate residual binarized neural networks using shortcut concatenation and shuffled grouped convolution [PDF]
PeerJ Computer Science, 2021 This article proposes a novel network model to achieve better accurate residual binarized convolutional neural networks (CNNs), denoted as AresB-Net.
HyunJin Kim
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Interpretable Convolutional Neural Networks [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 This paper proposes a method to modify traditional convolutional neural networks (CNNs) into interpretable CNNs, in order to clarify knowledge representations in high conv-layers of CNNs. In an interpretable CNN, each filter in a high conv-layer represents a certain object part.
Quanshi Zhang +2 more
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ETALON IMAGES: UNDERSTANDING THE CONVOLUTION NEURAL NETWORKS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 In this paper we propose a new technic called etalons, which allows us to interpret the way how convolution network makes its predictions. This mechanism is very similar to voting among different experts.
V. V. Molchanov +3 more
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FusionNet: A Convolution–Transformer Fusion Network for Hyperspectral Image Classification
Remote Sensing, 2022 In recent years, deep-learning-based hyperspectral image (HSI) classification networks have become one of the most dominant implementations in HSI classification tasks.
Liming Yang +6 more
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Physical Review Research, 2020 We perform theoretical and algorithmic studies for the problem of clustering and semisupervised classification on graphs with both pairwise relational information and single-point attribute information, upon a joint stochastic block model for synthetic ...
Pengfei Zhou, Tianyi Li, Pan Zhang
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Online social network user performance prediction by graph neural networks
IJAIN (International Journal of Advances in Intelligent Informatics), 2022 Online social networks provide rich information that characterizes the user’s personality, his interests, hobbies, and reflects his current state. Users of social networks publish photos, posts, videos, audio, etc. every day. Online social networks (OSN)
Fail Gafarov +2 more
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Powerset Convolutional Neural Networks
CoRR, 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 +2 more
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Research on Real-Time Face Recognition Algorithm Based on Lightweight Network
Jisuanji kexue yu tansuo, 2020 In order to achieve high-precision real-time face recognition on embedded and mobile devices, the advant-ages and disadvantages of common networks in face recognition are analyzed, and an efficient deep convolution neural network model Lightfacenet is ...
ZHANG Dian, WANG Haitao, JIANG Ying, CHEN Xing
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