Results 91 to 100 of about 250,191 (314)
Research on road extraction of remote sensing image based on convolutional neural network
EURASIP Journal on Image and Video Processing, 2019 Road is an important kind of basic geographic information. Road information extraction plays an important role in traffic management, urban planning, automatic vehicle navigation, and emergency management.
Yuantao Jiang
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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
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An Optimized Convolutional Neural Network for the 3D Point-Cloud Compression
Sensors, 2023 Due to the tremendous volume taken by the 3D point-cloud models, knowing how to achieve the balance between a high compression ratio, a low distortion rate, and computing cost in point-cloud compression is a significant issue in the field of virtual ...
Guoliang Luo +6 more
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Irregular Convolutional Neural Networks [PDF]
2017 4th IAPR Asian Conference on Pattern Recognition (ACPR), 2017 7 pages, 5 figures, 3 ...
Jiabin Ma +2 more
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Self-grouping convolutional neural networks [PDF]
Neural Networks, 2020 Although group convolution operators are increasingly used in deep convolutional neural networks to improve the computational efficiency and to reduce the number of parameters, most existing methods construct their group convolution architectures by a predefined partitioning of the filters of each convolutional layer into multiple regular filter groups
Qingbei Guo +3 more
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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 +14 more
wiley +1 more source
Large receptive field convolutional neural network for image super-resolution [PDF]
, 2017 This paper presents a new approach to Single Image Super Resolution (SISR), based upon Convolutional Neural Network (CNN). Although the SISR is ill-posed which can be seen as finding a non-linear mapping from a low to high dimensional space.
Wang Q(王强) +3 more
core
A convolutional neural network for automatic analysis of aerial imagery [PDF]
, 2014 This paper introduces a new method to automate the detection of marine species in aerial imagery using a Machine Learning approach. Our proposed system has at its core, a convolutional neural network. We compare this trainable classifier to a handcrafted
Amanda Hodgson +8 more
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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
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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
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