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Questions tagged [neural-networks]

For questions about a neural networks, such as ANNs, CNNs, RNNs, or any other machine learning components that qualifies as a neural networks in that they simulate key complexity handling aspects of biological neural networks in invertebrates.

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1answer
16 views

How much extra information can we conclude from a neural network output values?

Consider I have a 3 layers neural network. Input Layer containing 784 neurons. Hidden layer containing 100 neurons. Output layer containing 10 neurons. My objective is to make an OCR and I used ...
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0answers
8 views

Which pretrained embeddings version to choose ?

I want to use pretrained embeddings. Let's say FastText. But from the website, there is several versions available : Pre-trained word vectors learned on different sources can be downloaded below: ...
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1answer
66 views

Why are Neural Networks considered Artificially Intelligent?

Why in every aspect are we now considering Neural Networks as an Artificially Intelligent entity/program?
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8 views

Usefulness of Data augmentation for non-overfitting network [NLP]

(Maybe related : Usefulness of Dropout for non-overfitting network) My neural network does not overfit. Using Data augmentation in a non-overfitting network can increase its accuracy ? Note : I'm ...
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3answers
30 views

Batch mode vs mini-batch mode vs stochastic mode

Batch size is a term used in machine learning and refers to the number of training examples utilised in one iteration. The batch size can be one of three options: batch mode: where the ...
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0answers
10 views

Variable sized input-Multi Label Classification with Neural Network

I have a data input vector ( No Image classification) which size varys from 2 to 7 entrys. Every one of them belongs to a class Out of 7. So I have a variable Input size and a variable Output size. ...
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0answers
23 views

First perceptron learning algorithm

I struggle to find Rosenblatts perceptron training algorithm in any of his publications from 1967 - 1951, namely: [1] Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms [2] ...
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3answers
37 views

When are weights updated? (feed-forward neural network)

When am I supposed to update my weights? After each forward-, and backpropagation; and or after each completed batch? Furthermore, if I am supposed to update the weights both after each forward-, and ...
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1answer
23 views

How to perform neural network with output constraint?

Imagine a "simple" feedforward, fully connected neural network, with some input size, some number of hidden layers, and some # of neurons....etc BUT with a fixed number of output size (that is saying, ...
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1answer
19 views

Usefulness of Dropout for non-overfitting network

My neural network is simple enough and does not overfit. Dropout is a regularization technique for reducing overfitting in neural networks From Wikipedia Adding Dropout in a non-overfitting ...
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1answer
12 views

Neural Network for OMR?

I've created a neural net using the ConvNetSharp library which has 3 fully connected hidden layers. The first having 35 neurons and the other two having 25 neurons each, each layer with a ReLU layer ...
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0answers
10 views

What is the most common way \delta is defined as (in the context of a neural network)

Two highly reliable sources: Brilliant defines \delta as such: https://brilliant.org/wiki/backpropagation/ Meanwhile Nielsen defines it as such: http://neuralnetworksanddeeplearning.com/chap2.html ...
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0answers
15 views

How to understand marginal loglikelihood objective function as loss function (explanation of an article)?

I am reading article https://allenai.org/paper-appendix/emnlp2017-wt/ http://ai2-website.s3.amazonaws.com/publications/wikitables.pdf about training neural network and the loss function is mentioned ...
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0answers
22 views

Simple feed-forward nn does not learn

dataset can be retrieved here: https://www.kaggle.com/uciml/pima-indians-diabetes-database/downloads/diabetes.csv/1 ...
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1answer
29 views

Can we combine multiple different neural networks in one?

I want to make a kind of robotic brain i.e. a big neural network, which includes NLP model (for understanding human voice) , real-time object recognition (so it can identify particular object), face ...
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1answer
18 views

Why is there Transition layers in DenseNet?

The DenseNet architecture can be summarize with this figure : Why there is transition layers between each blocks ? In the papers, they justify the use of transition layers as follow : The ...
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2answers
45 views

How to improve testing accuracy when training accuracy is high?

Following-up my question about my over-fitting network My deep neural network is over-fitting : I have tried several things : Simplify the architecture Apply more (and more !) Dropout Data ...
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2answers
41 views

Understanding LSTM/RNN structure

In keras when we apply LSTM/RNN model, we specify the node [i.e.,LSTM(128)]. I have a doubt how it actually works. From the LSTM/RNN unfolding image or description, I found that each RNN cell take one ...
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1answer
50 views

Is there any pretrained model for emotion detection? [closed]

I would like to detect emotions (facial expressions) in videos using Python. I have used APIs like Microsoft/Oxford API and Affectiva but would like to use a pretrained model.
2
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1answer
17 views

Choosing Instance Semantic Detection

A fixed video camera records people moving through its field of view. The goal is to detect and track the head, in real-time as it moves through the video. The norm is there are many heads, which ...
2
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1answer
19 views

Maxpooling in inception?

Maxpooling is performed as one of the steps in inception which yields same output dimension as that of the input. Can anyone explain how this max pooling is performed?
2
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1answer
27 views

Would this work to prevent forgetting: train a neural net with N nodes. Then, add more nodes and stop training the original nodes

Would this work at all? Idea is to start training a neural net with some number of nodes. Then, add some new nodes and more layers and start training only the new nodes (or only modifying the old ...
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0answers
45 views

Extract particular pattern from the given text/paragraph using machine or deep learning

If there is given a one paragraph as a input and it extract a string from the paragraph,within a predefined range (i.e. a string that starts with three letters that a always fixed and ends with five ...
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1answer
42 views

Interpretation of a good overfitting score

As shown below, my deep neural network is overfitting : where the blue lines is the metrics obtained with training set and red lines with validation set Is there anything I can infer from the fact ...
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0answers
8 views

Pre priming a network for white space

When a human looks at a page. He notices the sets of letters are grouped together separated by white space. If the white space was replaced by another character say z, it would be harder to ...
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1answer
32 views

How should I label the classes in RNA?

I have a project, which is the keyboard biometrics of users. suppose I have 3 users, I do not know how to label in two types of class, (+ 1, -1). If I want to verify the identity to user1, my idea ...
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1answer
24 views

Inception neural network input layer confusion

According to the original paper on page 4, 224x224x3 image is reduced to 112x112x64 using a filter ...
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2answers
56 views

how to handle rectangle images in neural network?

Almost all the neural network architecture I have come across have a square input size of an image. like 32x32,64x64,128x128,....... Ideally we might not have a ...
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0answers
20 views

NEAT + Keras : reproducibility problem (World Models implementation)

I'm trying to apply the World Models architecture to the Sonic game (using the gym-retro library). My problem concerns the evolutionnary algorithm part that I use as the controller (worldmodels = ...
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3answers
45 views

How to detect a Neural Network will work with the whole dataset?

I want to implement a neural network on a big dataset. But training time is long (~1h30 per epoch). I'm still in the development process, so I don't want to wait such long time just to have poor ...
6
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4answers
120 views

Is it suitable to find inverse of last layer's activation function and apply it on the target output?

I have a neural network with the following structure: I am expecting specific outputs from the neural network which are the target values for my training. Let's say the target values are 0.8 for the ...
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0answers
12 views

Gradient of hinge loss function

With reference to the research paper entitled Sentiment Embeddings with Applications to Sentiment Analysis, I am trying to implement its sentiment ranking model in Python for which I am required to ...
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0answers
15 views

How to create Partially Connected NNs with prespecified connections using Tensorflow?

I'd like to implement a partially connected neural network with ~3-4 hidden layers (a sparse deep neural network?) where I can specify which node connects to which node from the previous/next layer. ...
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1answer
21 views

Update theta in a perceptron?

Is theta supposed to be updated in a perceptron, like the weights, and if so, what is the formula for this? I'm trying to make the perceptron learn AND and OR, but without updating theta, I don't ...
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3answers
82 views

Traffic signs dataset

I'm looking for annotated dataset of traffic signs. I was able to find Belgium, German and many more traffic signs datasets. The only problem is these datasets contain only cropped images, like this: ...
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1answer
28 views

Weight Normalization paper

I am trying to dissect paper about weight normalization: https://papers.nips.cc/paper/6114-weight-normalization-a-simple-reparameterization-to-accelerate-training-of-deep-neural-networks.pdf ...
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0answers
7 views

Stack for Automatic 3D Mesh Generation

Gist: Should I use LISP for a part of the following project. What are the other options. Me and a friend are planning to create a 3D Modelling Agent where a designer can :- Specify constrains on how ...
2
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2answers
90 views

Creating a self learning Mario Kart game AI?

I will be undertaking a project over the next year to create a self learning AI to play a racing game, currently the game will be Mario Kart 64. I have a few questions which will hopefully help me ...
2
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4answers
59 views

Using Convolutional Neural Networks for movement classification

I have programmed my first network for the MNIST dataset. I was wondering what the first approach would be to recognize certain movements. I have read about that the time dimension should be ...
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2answers
3k views

How fast is TensorFlow compared to self written neural nets?

I made my first neural net in C++ without any libraries. It was a net to recognize numbers from the MNIST dataset. In a 784 - 784 - 10 net with sigmoid function and 5 epochs with each 60000 samples, ...
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1answer
26 views

Is the cube root function suitable as a n activation function?

I am trying to design a neural network on Python. Instead of the sigmoid function which has a limited range, I am thinking of using the cube root function which has the following graph: Is this ...
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0answers
20 views

How does using neural network to improve evaluation function work?

I’ve seen some papers using neural network as evaluation function to evaluate game state. I wonder if they can value the state to train the neural network, isn’t the function that is used to value the ...
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1answer
37 views

predict waste generation

I am starting a project to predict the generation of urban waste. I have found very little information on this topic on the internet. I would be very useful advice on how to approach this topic, and ...
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1answer
37 views

Using linear activation function in output layer

I have a simple question about the choice of activation function for the output layer in feed-forward neural networks. I have seen several codes, where the choice of activation function for the ...
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0answers
28 views

Autoencoder why it is special for image decoding?

I have read about auto encoder. Understood what is encoding part, and decoding part, and the latent space. Now, i tried to implement this in keras. Below is the code. ...
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0answers
28 views
1
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1answer
22 views

Which marketing related classifictation challenges is a feed forward neural network suited to sovle?

I am trying to think of some marketing related classification challenges that a feed forward neural network would be suited for. Any ideas?
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0answers
16 views

Does the graphic become convex or concave in case we have a negative or positive loss in neural network?

For example, we have a positive loss and it's convex and we have a negative loss and it's concave. I know that if we have an MSE as our cost function result is always positive. But what if we have a ...
2
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1answer
79 views

Variations of the squared error function

Depending on the source I find people using different variations of the "squared error function", how come that be? Variation 1 Variation 2 Notice that it is being devided by 1 over m as ...
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1answer
27 views

Neural Network on EV3 Mindstorm without 3rd Party Software

I am working on a prototype for an Ev3 Neural Network. Because for competitions, we are not allowed to use Bluetooth or Wifi connections, the neural network must be made with the Ev3 block-based ...