常见优化器, Encoder和Decoder
文章参考论文:Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation。 在很多时序分类(Temporal Classification)的应用中,输入数据X和输出数据Y的标签长度并不相等,而且不存在单调的映射关系,例如机器翻译,对话系统等等。为了解决这个问题,作者提出了RNN Encoder-Decoder模型,RNN Encod...
我们加一个decoder解码器,这时候decoder就会输出一个信息,那么如果输出的这个信息和一开始的输入信号input是很像的(理想情况下就是一样的),那很明显,我们就有理由相信这个code是靠谱的。所以,我们就通过调整encoder和decoder的参数,使得重构误差最小,这时候我们就得到了输入input信号的第一个表示了,也就是编码code了。
2.2 解码器 Decoder 至于解码器 Decoder, 我们也能那它来做点事情. 我们知道, 解码器在训练的时候是要将精髓信息解压成原始信息, 那么这就提供了一个解压器的作用, 甚至我们可以认为是一个生成器 (类似于GAN). 那做这件事的一种特殊自编码叫做 variational autoencoders, 你能在这里找到他的具体说明. 有一个...
Deep learning, which is a subfield of machine learning, has opened a new era for the development of neural networks. The auto-encoder is a key component of deep structure, which can be used to realize transfer learning and plays an important role in both unsupervised learning and non-linear...
对于Linear Decoders设定,a(3) = z(3)则称之为线性编码 sigmoid激活函数要求输入范围在[0,1]之间,某些数据集很难满足,则采用线性编码 此时,误差项更新为
Key words: remote sensing road extraction deep learning semantic segmentation Encoder-Decoder network 道路作为交通的主要组成部分,在人类各项活动中发挥着不可替代的作用。在现代社会中,道路也是地图和地理信息系统中重要的标识对象。随着交通地理信息系统的建设,道路的自动提取技术随之出现并不断发展[1]。及时而完备...
We have demonstrated that training of deep encoder-decoder convolutional networks overcomes complexities associated with multiple nuclear phenotypes, where we evaluate alternative architecture of deep learning for an improved performance against the simplicity of the design. In addition, improved nuclear ...
Decoder network, specified as adlnetwork(Deep Learning Toolbox)object. The network must have a single input and a single output. Name-Value Arguments Specify optional pairs of arguments asName1=Value1,...,NameN=ValueN, whereNameis the argument name andValueis the corresponding value. Name-valu...
machine-learning deep-learning jupyter keras jupyter-notebook cnn lstm floydhub seq2seq cnn-keras encoder-decoder Updated Aug 16, 2024 HTML bentrevett / pytorch-seq2seq Star 5.4k Code Issues Pull requests Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch ...