Convolutional neural networks (CNNs) are among the most commonly investigated models in computer vision. Deep CNNs yield high computational performance, but their common issue is a large size. For solving this problem, it is necessary to find effective compression methods which can effectively ...
To deploy deep CNNs on mobile devices, we present a simple and effective scheme to compress the entire CNN, which we call one-shot whole network compression. The proposed scheme consists of three steps: (1) rank selection with variational Bayesian matrix factorization, (2) Tucker decomposition ...
我们建议使用权重共享来减少频域中的参数数量。对于频率表示中的滤波器,我们希望将模型参数的数量精确地减少到存储在权重向量w中的K个值,其中K«mXnXd^2。为了实现这一点,我们随机地将值从w分配给V中的每个滤波器频率权重。这种随机权重共享的实现将为V引入辅助矩阵以跟踪权重分配,使用显着的额外存储器。为了解决...
2020-ICLR-FSNet Compression of Deep Convolutional Neural Networks by Filter Summary 来源:ChenBong 博客园 Institute:Arizona State University,Microsoft Resea
JPEG is one of the most commonly used standards among lossy image compression methods. However, JPEG compression inevitably introduces various kinds of artifacts, especially at high compression rates, which could greatly affect the Quality of Experience (QoE). Recently, convolutional neural network (CNN...
Compression Artifacts Reduction by a Deep Convolutional Network 阅读笔记 ReductionbyaDeepConvolutionalNetwork》是2015年港中文汤晓鸥组发的一篇针对压缩图像的人工痕迹修复的文章,其主要基于之前对超分辨的SRCNN,提出了AR-CNN,该深度神经网络共4层,依次是Feature extraction层(filter: 64*9*9)、Feature enhancement层...
Code is available at https://github.com/Clarkxielf/FSConv-Flexible-and-Separable-Convolution-for-Convolutional-Neural-Networks-Compression. Introduction Over the past few years, CNNs have shown extraordinary ability in the community of computer vision, such as image classification [1], object ...
MSCNN论文解读-A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection,程序员大本营,技术文章内容聚合第一站。
A Pseudo-Blind Convolutional Neural Network for the Reduction of Compression Artifacts 总结 非盲图像恢复子网络 压缩系数预测子网络 实验 总结 问题:HEVC压缩视频的盲恢复。 背景: 当前方法都需已知量化参数QP,intra/inter coding,prediction unit sizes,deblocking filter on/off等。
This example shows how to compress a convolutional neural network (CNN) to prepare it for deployment on an embedded system. Deploying deep learning models on embedded systems can be challenging due to the limited memory and processing power of embedded systems. Model compression addresse...