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542 results
  • Changes in running kinematics and kinetics after a 12-week running program for beginners. [Journal Article]
    Sports Biomech 2019; :1-11Maas E, Vanwanseele B
  • The effect of running training on running kinematics and kinetics in novice runners has not yet been investigated. Previous studies have shown that novice runners are less economical and more prone to injury compared to well-trained runners. Since running economy (RE) and running injury risk have been associated with biomechanical variables that may be trainable, the purpose of this study was to …
  • Deep Learning for Low-Dose CT Denoising Using Perceptual Loss and Edge Detection Layer. [Journal Article]
    J Digit Imaging 2019Gholizadeh-Ansari M, Alirezaie J, Babyn P
  • Low-dose CT denoising is a challenging task that has been studied by many researchers. Some studies have used deep neural networks to improve the quality of low-dose CT images and achieved fruitful results. In this paper, we propose a deep neural network that uses dilated convolutions with different dilation rates instead of standard convolution helping to capture more contextual information in f…
  • Two-Stream Deep Hashing With Class-Specific Centers for Supervised Image Search. [Journal Article]
    IEEE Trans Neural Netw Learn Syst 2019Deng C, Yang E, … Tao D
  • Hashing has been widely used for large-scale approximate nearest neighbor search due to its storage and search efficiency. Recent supervised hashing research has shown that deep learning-based methods can significantly outperform nondeep methods. Most existing supervised deep hashing methods exploit supervisory signals to generate similar and dissimilar image pairs for training. However, natural …
  • Neural network model combined with pupil recovery for Fourier ptychographic microscopy. [Journal Article]
    Opt Express 2019; 27(17):24161-24174Sun M, Chen X, … Xuan L
  • Fourier ptychographic microscopy (FPM) is a recently developed imaging approach aiming at circumventing the limitation of the space-bandwidth product (SBP) and acquiring a complex image with both wide field and high resolution. So far, in many algorithms that have been proposed to solve the FPM reconstruction problem, the pupil function is set to be a fixed value such as the coherent transfer fun…
  • Reinforcement Learning With Low-Complexity Liquid State Machines. [Journal Article]
    Front Neurosci 2019; 13:883Ponghiran W, Srinivasan G, Roy K
  • We propose reinforcement learning on simple networks consisting of random connections of spiking neurons (both recurrent and feed-forward) that can learn complex tasks with very little trainable parameters. Such sparse and randomly interconnected recurrent spiking networks exhibit highly non-linear dynamics that transform the inputs into rich high-dimensional representations based on the current …
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