The research concerns the use of machine learning algorithms for multiscale coding of digital video sequences. Based on machine learning, the digital image coder is generalized to the coding of video sequences. To this end, we offer an algorithm that allows for videoframes interdependency by ...
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[65]提出了一个基于更深并分组分段插值方法变异CNN (GVCNN)的one-for-all分数插值网络,通过处理不同的QP和亚像素位置来提高插值通用性。对于RA、LDB和LDP配置,它实现了0.9%、1.2%和2.2%的平均BDBR增益。然而,编码器和解码器的复杂性增加到是原来HEVC的5.29和1548.58倍,这看起来是不可负担的。
fori=1:size(X,2), mu(i)=mean(X(:,i)); sigma(i)=std(X(:,i)); X_norm(:,i)=(X_norm(:,i)-mu(i))/sigma(i); end; % === end 2. Computing Cost (for Multiple Variables) && Gradient Descent (for Multiple Variables)
Neural generative models can be used to learn complex probability distributions from data, to sample from them, and to produce probability density estimates. We propose a computational framework for developing neural generative models inspired by the the
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