Results 11 to 20 of about 1,532,152 (301)
Fully convolutional neural nets in-the-wild [PDF]
The ground breaking performance of fully convolutional neural nets (FCNs) for semantic segmentation tasks has yet to be achieved for landcover classification, partly because a lack of suitable trai...
Simms, Daniel M.
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A method for superfine pavement crack continuity detection based on topological loss
Deep convolutional neural networks have become a popular tool for the automatic detection of pavement cracks. Despite their widespread use, the models currently available tend to emphasize pixel‐level classification accuracy for cracks, often overlooking
Guohui Jia +4 more
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ROADSIDE FOREST MODELING USING DASHCAM VIDEOS AND CONVOLUTIONAL NEURAL NETS [PDF]
Tree failure is a primary cause of storm-related power outages throughout the United States. Roadside vegetation management is therefore critical to electric utility companies to prevent power outages during extreme weather conditions. It is difficult to
D. Joshi, C. Witharana
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SA-Net: Shuffle Attention for Deep Convolutional Neural Networks [PDF]
Attention mechanisms, which enable a neural network to accurately focus on all the relevant elements of the input, have become an essential component to improve the performance of deep neural networks. There are mainly two attention mechanisms widely used in computer vision studies, \textit{spatial attention} and \textit{channel attention}, which aim ...
Qing-Long Zhang, Yu-Bin Yang
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Human stability assessment and fall detection based on dynamic descriptors
Fall detection systems use a number of different technologies to achieve their goals. This way, they contribute to better life conditions for the elderly community.
Jesús Gutiérrez +2 more
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Rail transit has many advantages, such as large passenger capacity, convenience, safety, and environmental protection, making it the preferred travel mode for most passengers.
Xuanrong Zhang +3 more
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SRI3D: Two‐stream inflated 3D ConvNet based on sparse regularization for action recognition
Although most state‐of‐the‐art action recognition models have adopted a two‐stream 3D convolutional structure as a backbone network, few works have studied the impact of loss functions on action recognition models.
Zhaoqilin Yang +4 more
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Evaluating Age Estimation Using Deep Convolutional Neural Nets
Ignacio Arganda-Carreras
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LiteDEKR: End‐to‐end lite 2D human pose estimation network
The 2D human pose estimation plays an important role in human‐computer interaction and action recognition. Although the method based on high‐resolution network has superior performance, there is still room for improvement in terms of speed and ...
Xueqiang Lv +5 more
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Deep Net Tree Structure for Balance of Capacity and Approximation Ability
Deep learning has been successfully used in various applications including image classification, natural language processing and game theory. The heart of deep learning is to adopt deep neural networks (deep nets for short) with certain structures to ...
Charles K. Chui +4 more
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