Input layer is the first layer of any neural network and contains the input. Use this tag for asking questions related to this layer of the neural network.
Questions tagged [input-layer]
15 questions
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Why is the input layer of a neural network usually not counted?
I came across the following statement from the caption of figure 7.8 from the textbook Neural Networks and Neural Language Models
the input layer is usually not counted when enumerating layers
Why is the input layer excluded from counting?
Is the…
hanugm
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Input encoding for continuous variables
Say I have some inputs to my model that are continuous variables. What is a good way of representing them in input neurons so that the network can represent and learn various functions effectively?
A standard approach is to simply re-scale the input…
Tomek Czajka
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Is there any way to force one input have more effect on model?
Now I am working on building a deep learning model for a regression problem. I used 50 inputs and try to add one new categorical input. The problem is that this one input is much more important than other inputs. I want to make it more influential…
taegyun kim
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Is it a good practice to split sparse from dense features?
I have a mixture of real (float) and categorical features to use as input in a neural network. I encode the categorical features using one-hot / multi-hot encoding.
If I want to use all the features as input what is usually/empirically the best…
Michael
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How can a neural network learn to play a game with non-constant number of non-trivial entities?
Suppose you are training a neural network to play a game (like AlphaStar playing StarCraft). The game contains a non-constant number of entities, whose attributes change, and perhaps which have non-constant number of attributes.
For example, using…
spraff
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What is the channel dimension other than color representation in Conv2D? Shall I use Conv3D instead?
I have grayscaled image, specifically medical data ultrasonography.
In the context of medical domain, there are techniques to capture data that called "View". It's like point of views of CCTVs with different placement when capturing image. So, there…
Muhammad Ikhwan Perwira
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What is the best way to train a neural network with a variable number of inputs?
Suppose I have a neural network with 5 inputs: [A,B,C,D,E]
There is only 1 output. The expected accuracy of the model should increase when all 5 inputs are available, but often not all 5 inputs are available. For example, I might have case where I…
user18959
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Is data useless for a neural network if some inputs are derivatives of other inputs?
That is, if some of the inputs to a neural network can be calculated by a pre-determined function whose variables are other inputs, then are those specific inputs useless?
For example, suppose there are three inputs, $x_1$, $x_2$ and $x_3$. If $x_3$…
BlueSnake
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Neural networks with sparse inputs
I have a task I want to solve with neural networks. The task is predicting a certain vector of dimension K. The problem is that the inputs to the networks are sparse.
The input is a vector of size N, where N is huge (> 1M) and for most cases, the…
Ant
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Temporally Non-Aware RNN
I am trying to classify whether or not a specific object is in panoramic photos. The issue is, a panoramic photo can be any width, so the input to my neural network can't be fixed in that dimension.
I've been using RNNs (QRNNs to be specific, as I…
user55176
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How can Siamese Neural Networks accept a variable number of inputs?
Traditionally, Siamese Neural Networks have two inputs. With some tweaking, you can get them to accept any number of inputs. What I don't understand is how to get them to accept variable numbers of inputs. I've seen a couple of research papers (most…
GameDungeon
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Correctly input additional values into CNN
I understand that in order to add additional inputs to a CNN, e.g. in self driving, I can append the data to a flattened layer after the convolutions and before the fully connected layers.
However, a few things confuse me. In a paper the authors…
Benjoyo
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How to handle random order of inputs and get same output?
I am a beginner with DL. I did some tutorials and I know the basics of TensorFlow. But I have a problem understanding how to construct more advanced NNs.
Let's say I have 6 inputs and a list of 500 names from which you can pick any, but only 6 at…
tech2097
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Is there any difference between 'input' and 'conditional input' in the case of neural networks?
In the research paper titled Conditional Generative Adversarial Nets by Mehdi Mirza and Simon Osindero, there is a notion of conditioning a neural network on a class label.
It is mentioned in the abstract that we need to simply feed extra input $y$…
hanugm
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Using a Neural Network (LSTM) to approve/reject word-type sequences
I would like to train an LSTM neural network to either "approve" or "reject" a string based on the word-type sequence.
For instance: "Mike's Airplane" would output "approved", but "Airplane Mike's" would output "reject".
My method for doing this is…
Michael Lyons
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