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how to use multiple input layers in DAG net as shown in the figure

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I have DAG graph with two paths of layers inside it.
I am planning to feed this DAG with two types of data (D1, D2) but I can't do it as the DAG in matlab accept just one input layer.
I need to form a layer such as:
I noticed that there is a custom network that can provide a network with multiple inputs but how can I connect between this network and DAG graph? or how could I use DAG with two inputs?
  4 Kommentare
Ville Laukkanen
Ville Laukkanen am 5 Dez. 2017
This would be nice to have an answer to.
I have a similar situation with three image + three float-variables regression case. We're trying to estimate the output of an industrial process with images of material flows in from three different lines and their respective line-speed (float). I get the true output result much later. Would like to train the whole image regression thing together.
Maybe some modified version of LSTM would work or perhaps some funny layer which would decompose the input to six different layergraph-lines, but I can't find a way to do this in MatLab.
On Python Tensorflow there is the node structure and inputs given in dictionary (matlabs' struct). Would there be a way to do this in Matlab? - Input to several points in an layer graph.
Kenta am 29 Mär. 2020
As of 2019b, you can use custom training loop which allows you to do multi-input CNN.
This shows a demo to classify images with two-path sequence layers using two kinds of input images.

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Akzeptierte Antwort

Mahmoud Afifi
Mahmoud Afifi am 10 Feb. 2019
One idea is to feed the network with concatenated inputs (e.g., image1;image2) then create splitter layers that split each input. The problem here is that you have to feed the network with .mat files, not image paths. Another idea is to store your images as tiff files which can hold 4 channels. In this case, you can store a colored image (3 channel) and a grayscale one. Have a look at this example .. see twoStream.m file.
  5 Kommentare
dinial utami
dinial utami am 14 Jun. 2020
Mr, you just make multiple input in convolution, but not in trainNetwork Mr?
I see in trainNetwork just rever to one image.
miao li
miao li am 20 Mai 2021
Hello, I have a question, how to separate each channel using 1X1 convolution? I think that each convolutional layer operates on 6 channels separately and then adds them, but the channels cannot be extracted.

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Weitere Antworten (5)

Mahmoud Afifi
Mahmoud Afifi am 28 Okt. 2019
Bearbeitet: Mahmoud Afifi am 29 Okt. 2019
I just released an example Matlab code of how to implemenet multiple-input CNN in Matlab 2019b. You can find it here:
please if it works for you, accept this answer.
  1 Kommentar
dinial utami
dinial utami am 14 Jun. 2020
thank you for your helping Mr.
in the code you have share, has multiple input in layer. not in trainNetwork.
Mr, can you help if we has 3 input in different image for training set, we set 3 input layers, but we can't set 3 training set. in the reality we need 3 input layers, and 3 training set.
thank you Mr. Mahmoud Afifi

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Shounak Mitra
Shounak Mitra am 8 Okt. 2018
Hi Marcello and Arjun,
Support for multiple Input layers are not supported as of the 18b release. We are working on it and it should be available soon.
Thanks Shounak
  2 Kommentare
abir zendagui
abir zendagui am 6 Jan. 2019
Is the multiple input layers are really supported now (In 18b)? if it' is the case ,how this is done please?
Bodo Rosenhahn
Bodo Rosenhahn am 16 Mai 2019
are multiple input /output layers for DAG networks supported in 19a ? Can you provide an example ?

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Bernhard Suhm
Bernhard Suhm am 12 Dez. 2017
Modeling DAG graphs with multiple inputs and/or outputs is currently not supported in our deep learning framework, but we are working on it. So hold your breath for one of the next releases.
  5 Kommentare
Marcello Venzi
Marcello Venzi am 20 Sep. 2018
Hello, can you please comment if multiple input layers are now supported (as of maltab 2018b)? I could not find this option in the documentation.

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Yanhui Guo
Yanhui Guo am 24 Okt. 2018
In the DAGNetwork file, I found the property: InputLayerIndices. In the fasterrcnn, I also found two input for this network. I am wondering if matlab2018b has an indirect way to support multiple inputs? Thanks.

sinan salim
sinan salim am 4 Aug. 2020
hi is there any update to manage multi-input layer >>because i want use different classes each 2 classes have to be assign for separate input layer

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