Results 41 to 50 of about 156,643 (272)
Journal of King Saud University - Computer and Information Sciences, 2022 Modern day computer vision tasks requires efficient solution to problems such as image recognition, natural language processing, object detection, object segmentation and language translation. Symbolic Artificial Intelligence with its hard coding rules is incapable of solving these complex problems resulting in the introduction of Deep Learning (DL ...
Mensah Kwabena Patrick +3 more
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Malware Detection Based on the Feature Selection of a Correlation Information Decision Matrix
Mathematics, 2023 Smartphone apps are closely integrated with our daily lives, and mobile malware has brought about serious security issues. However, the features used in existing traffic-based malware detection techniques have a large amount of redundancy and useless ...
Kai Lu, Jieren Cheng, Anli Yan
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Reconfigurable Component-based Middleware for Networked Embedded Systems [PDF]
, 2007 Next generation embedded systems will be composed of large numbers of heterogeneous devices. These will typically be resource-constrained (such as sensor motes), will use different operating systems, and will be connected through different types of ...
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Image Super-Resolution Using Capsule Neural Networks
IEEE Access, 2020 Convolutional neural networks (CNNs) have been widely applied in super-resolution (SR) and other image restoration tasks. Recently, Hinton et al. proposed capsule neural networks to resolve the problem of viewpoint variations in image classification ...
Jui-Ting Hsu, Chih-Hung Kuo, De-Wei Chen
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IEEE Access, 2021 The improvement of remote sensing scene classification(RSSC) by effectively extracting discriminant representations for complex and diverse scenes remains a challenging task. The capsule network(CapsNet) can encode the spatial relationship of features in
Chunyuan Wang +4 more
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How to Accelerate Capsule Convolutions in Capsule Networks
, 2021 How to improve the efficiency of routing procedures in CapsNets has been studied a lot. However, the efficiency of capsule convolutions has largely been neglected. Capsule convolution, which uses capsules rather than neurons as the basic computation unit, makes it incompatible with current deep learning frameworks' optimization solution.
Chen, Zhenhua +3 more
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Unsupervised Odometry and Depth Learning for Endoscopic Capsule Robots
, 2018 In the last decade, many medical companies and research groups have tried to convert passive capsule endoscopes as an emerging and minimally invasive diagnostic technology into actively steerable endoscopic capsule robots which will provide more ...
Almalioglu, Yasin +6 more
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Road marking extraction in UAV imagery using attentive capsule feature pyramid network
International Journal of Applied Earth Observations and Geoinformation, 2022 Accurately and precisely delineating road-markings from very high spatial resolution unmanned aerial vehicle (UAV) images face many challenges, such as complex scenarios, diverse road marking sizes and shapes, and absent and occluded road markings.
Haiyan Guan +6 more
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Multi-labeled Relation Extraction with Attentive Capsule Network
, 2018 To disclose overlapped multiple relations from a sentence still keeps challenging. Most current works in terms of neural models inconveniently assuming that each sentence is explicitly mapped to a relation label, cannot handle multiple relations properly
Jia, Weijia +3 more
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Image Colorization by Capsule Networks [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2019 Accepted to New Trends in Image Restoration and Enhancement(NTIRE) Workshop at CVPR ...
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