Results 101 to 110 of about 5,349,001 (214)
Large receptive field convolutional neural network for image super-resolution
, 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
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, 2020 This paper explores the value of weak-ties in classifying academic literature with the use of graph convolutional neural networks. Our experiments look at the results of treating weak-ties as if they were strong-ties to determine if that assumption ...
Gita Sukthankar +2 more
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Rede neural por convolução para reconstrução estéreo [PDF]
, 2000 Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico.Para a modelagem de redes neurais para aplicações de problemas invariantes à translação utilizamos restrições de compartilhamento de pesos.
Otuyama, Júlio Massayuki
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Lip Image Segmentation Based on a Fuzzy Convolutional Neural Network
, 2020 Research has shown that the human lip and its movements are a rich source of information related to speech content and speaker's identity. Lip image segmentation, as a fundamental step in many lip-reading and visual speaker authentication systems, is of ...
Liew, AWC, Wang, S, Guan, C
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Chinese herbal medicines are the treasure of Chinese traditional medicine, which contains active ingredients that have significant therapeutic effects for many diseases.
Lulu Lv +8 more
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, 2023 A model of a convolutional neural network, a database for training a neural network, and a software tool for classifying the presence of a medical mask on a person’s face, which allows recognizing the presence of a medical mask from the transmitted image,
Hryhorenko, Y.S. +5 more
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Wavelet Convolutional Neural Networks
CoRR, 2018 Spatial and spectral approaches are two major approaches for image processing tasks such as image classification and object recognition. Among many such algorithms, convolutional neural networks (CNNs) have recently achieved significant performance improvement in many challenging tasks. Since CNNs process images directly in the spatial domain, they are
Shin Fujieda +2 more
openaire +3 more sources
Frequency-Domain and Spatial-Domain MLMVN-Based Convolutional Neural Networks
AlgorithmsThis paper presents a detailed analysis of a convolutional neural network based on multi-valued neurons (CNNMVN) and a fully connected multilayer neural network based on multi-valued neurons (MLMVN), employed here as a convolutional neural network in the
Igor Aizenberg, Alexander Vasko
doaj +1 more source
A Convolutional Neural Network Using Anterior Segment Photos for Infectious Keratitis Identification [PDF]
Vannarut Satitpitakul,1,2 Apiwit Puangsricharern,3 Surachet Yuktiratna,3 Yossapon Jaisarn,4 Keeratika Sangsao,4 Vilavun Puangsricharern,1,2 Ngamjit Kasetsuwan,1,2 Usanee Reinprayoon,1,2 Thanachaporn Kittipibul1,2 1Center of Excellence for Cornea and Stem
Satitpitakul V +8 more
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Convolutional neural network parameters.
, 2020 Convolutional neural network parameters.
Martin Hrabe De Angelis (8293275) +36 more
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