Efficient convolutional sparse coding. In Pro- ceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pages 7173-7177, May 2014. doi:10.1109/ICASSP.2014.6854992.B. Wohlberg, "Efficient convolutional sparse coding," in Proc. IEEE Int. Conf. Acoust. Speech ...
The separation of signal and noise is realized by convolution sum between the learned filters and the corresponding sparse feature maps. The paper first introduces the basic theory of CSC, and then gives a denoising process of efficient convolutional sparse coding, finally, we evaluate the denoising...
因此,SSNN-BP 使 BP 与纯基于脉冲的神经形态硬件兼容。 6 Unsupervised energy disaggregation via convolutional sparse coding 标题:通过卷积稀疏编码进行无监督能量分解 文章链接:https://arxiv.org/abs/2207.09785 摘要:在这项工作中,提出了一种在配备智能电表的私人家庭中进行无监督能源分解的方法。该方法旨在将功...
The high energy-efficient bit-sparse accelerator design is proposed to address the performance bottleneck of current bit-sparse architectures. Firstly, a coding method and corresponding circuit are proposed to enhance the bit-sparsity of
than other natural images. This has been explored via diverse computational approaches: in the field of computer graphics12, via entropy-based methods13,14,15, using wavelet approaches16,17, and, more recently, in machine learning implementations based on deep convolutional neural networks18,19,20...
where Kˆ is the depthwise convolutional kernel of size DK × DK × M where the mth filter in Kˆ is applied to the mth channel in F to produce the mth channel of the filtered output feature map Gˆ . 其中K^是尺寸为DK x DK x M的深度卷积核,其中K^应用到F中第m个通道来产生滤...
The deployment of deep convolutional neural networks (CNNs) in many Real-World applications is largely hindered by their high computational cost. In this paper, we propose a novel learning scheme for CNNs to simultaneously 1) reduce the model size; 2) decrease the run-time memory footprint; ...
一个简单解释是:"经过BN层的输出要经过的计算是\gamma*x+\beta,\gamma小输出就小,也就意味着这个输出对最终结果影响小",具体内容可参考《Learning Efficient Convolutional Networks through Network Slimming》的这篇论文原文以及知乎文章的评论区,我并没有细究...
The efficient coding hypothesis has become a standard explanation for the emergence of these non-homogeneous sensitivity patterns3. It predicts that sensory systems should preferentially encode more common aspects of the world at the expense of less common aspects, as this is the most efficient way ...
Although convolutional representation of multiscale sparse tensor demonstrated its superior efficiency to accurately model the occupancy probability for the compression of geometry component of dense object point clouds, its capacity for representing sparse LiDAR point cloud geometry (PCG) was largely limited...