Results 11 to 20 of about 52,973 (279)
SA-Net: Shuffle Attention for Deep Convolutional Neural Networks [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 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, spatial attention and channel attention, which aim to capture the ...
Qing-Long Zhang, Yu-Bin Yang
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IET Intelligent Transport Systems, 2023 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
IET Image Processing, 2023 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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Fully convolutional neural nets in-the-wild [PDF]
Remote Sensing Letters, 2020 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...
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RC-Net: A Convolutional Neural Network for Retinal Vessel Segmentation [PDF]
2021 Digital Image Computing: Techniques and Applications (DICTA), 2021 Over recent years, increasingly complex approaches based on sophisticated convolutional neural network architectures have been slowly pushing performance on well-established benchmark datasets. In this paper, we take a step back to examine the real need for such complexity.
Tariq Mahmood Khan +2 more
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LiteDEKR: End‐to‐end lite 2D human pose estimation network
IET Image Processing, 2023 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
Frontiers in Applied Mathematics and Statistics, 2019 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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Communication-Optimal Convolutional Neural Nets
CoRR, 2018 Efficiently executing convolutional neural nets (CNNs) is important in many machine-learning tasks. Since the cost of moving a word of data, either between levels of a memory hierarchy or between processors over a network, is much higher than the cost of an arithmetic operation, minimizing data movement is critical to performance optimization.
James Demmel, Grace Dinh
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Efficient ear alignment using a two‐stack hourglass network
IET Biometrics, 2023 Ear images have been shown to be a reliable modality for biometric recognition with desirable characteristics, such as high universality, distinctiveness, measurability and permanence. While a considerable amount of research has been directed towards ear
Anja Hrovatič +3 more
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Neural waves and computation in a neural net model I: Convolutional hierarchies
Journal of Computational Neuroscience, 2023 Abstract The computational resources of a neuromorphic network model introduced earlier are investigated in the context of such hierarchical systems as the mammalian visual cortex. It is argued that a form of ubiquitous spontaneous local convolution, driven by spontaneously arising wave-like activity---which itself promotes local ...
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