Structured feature sparsity training for convolutional neural network compressionConvolutional neural networkCNN compressionStructured sparsityPruning criterionConvolutional neural networks (CNNs) with large mo
Neural Compression-Based Feature Learning for Video Restoration Cong Huang, Jiahao Li, Bin Li, Dong Liu, Yan Lu CVPR 2022|May 2022 下载BibTex How to efficiently utilize the temporal features is crucial, yet challenging, for video restoration. The temporal features usually contain vario...
These methods produce high coding efficiency for general audio while supporting various bitrates, sampling rates, and real-time compression. 长期以来低比特率参数语音和音频编解码器一直在被研究(Atal & Hanauer, 1971; Juang & Gray, 1982),但它们的质量一直受到严重限制。 尽管取得了一些进展(Griffin 和 ...
SqueezeNet 的核心在于 Fire module,Fire module 由两层构成,分别是 squeeze 层+expand 层,squeeze 层是一个 1×1 卷积核的卷积层,对上一层 feature map 进行卷积,主要目的是减少 feature map 的维数,expand 层是 1×1 和 3×3 卷积核的卷积层,expand 层中,把 1×1 和 3×3 得到的 feature map 进行 ...
Binary neural networks have a number of advantages compared to standard neural networks including rapid one-pass training, high levels of data compression, computational simplicity, network transparency, a partial match capability and a scalable architecture that can be easily mapped onto high performance...
NNI (Neural Network Intelligence)is a lightweight but powerful toolkit to help usersautomateFeature Engineering,Neural Architecture Search,Hyperparameter TuningandModel Compression. The tool manages automated machine learning (AutoML) experiments,dispatches and runsexperiments' trial jobs generated by tuning ...
As expected, overall performance dropped with increased compression factor. However, while for compression factor 2, there was still no significant difference between stimulus-driven and endogenous theta-gamma coupling, a significant difference emerged for compression factor 3, (mean difference = 1.74% ...
and environmental factors. All pavements have a base that contains a subgrade composed of one or more types of soils. The distribution of loads across various layers leads to deformation, compression, and distortion of subgrade soils7. During the initial phase of vehicle traffic loading, the subgr...
NNI (Neural Network Intelligence)is a lightweight but powerful toolkit to help usersautomateFeature Engineering,Neural Architecture Search,Hyperparameter TuningandModel Compression. The tool manages automated machine learning (AutoML) experiments,dispatches and runsexperiments' trial jobs generated by tuning ...
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. python data-science machine-learning deep-learning neural-network tensorflow machine-learning-algorithms pytorch distributed hyperparameter...