Is there a 'Pixel classification layer' equivalent for 1 dimensional vector 'Deep Network Designer'?
1 回表示 (過去 30 日間)
古いコメントを表示
I am trying to test a theory where my input is a 1-dimensional vector with N elements. I wanto to use an 'Auto-encoder' like network structure to compute a new N element vector which should ideally match the output sequence. Also, each one of the N outputs can belong to one of three classes. Is there a way to do this?
0 件のコメント
回答 (1 件)
Raunak Gupta
2020 年 8 月 7 日
編集済み: Raunak Gupta
2020 年 8 月 7 日
Hi,
There is 1-D convolutional layer which you can build using the methods described here and here. This way a encoder and decoder network can be built in 1-D. After that you can attach pixel classification layer at the end to complete the workflow. Since the output size is calculated automatically by pixelClassificationlayer, the 1-D input size will also work (Make sure to give appropriate batch size too). Using 1-D convolutional layer described in above answers you can build the autoencoder model.
0 件のコメント
参考
カテゴリ
Help Center および File Exchange で Deep Learning Toolbox についてさらに検索
製品
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!