Questions tagged [neural-networks]

For questions about a artificial networks, such as MLPs, CNNs, RNNs, LSTM, and GRU networks, their variants or any other AI system components that qualify as a neural networks in that they are, in part, inspired by biological neural networks.

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1answer
28 views

Is it possible to use deeplearning with spark (with a distributed databases as HDFS or Cassandra)?

If it is possible, will it be really useful or the model will end up converging very early(with a typical optimum learning rate) ? Any content on this topic will be helpful for me.
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1answer
37 views

Is it possible to derive meaning from text by providing multiple ways of saying the same thing to a neural network?

Let's say I feed a neural network with multiple string sentences that mean roughly the same thing but are formulated differently. Will the neural network be able to derive patterns of meaning in the ...
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2answers
52 views

Is this model overfitted or not?

I am training a neural network and plot model accuracy and model loss. I am a little confused about overfitting. Is my model overfitted or not? how can I interpret it EDIT: here is a sample of my ...
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1answer
57 views

Is there a way to ensure that my model is able to recognize an unseen example?

My question is more theoretical than practical. Let's say that I am training my cat classifier with a dataset that I feel is pretty representative of cat images in general. But then a new breed of cat ...
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0answers
20 views

My CTC loss model's loss stagnates and then outputs only blank characters

I am trying to implement BaiDu's DeepSpeech1 in keras using CTC loss, my code is below: ...
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0answers
13 views

How to pad sequences during training for an encoder decoder model

I've got an encoder-decoder model for character level English language spelling correction, it is pretty basic stuff with a two LSTM encoder and another LSTM decoder. However, up until now, I have ...
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1answer
22 views

deep learning with kfold cross validation with epochs

I am new into neural networks, I want to use K-fold cross-validation to train my neural network. I want to use 5 folds 50 epochs and a batch size of 64 I found a function in scikit for k-fold cross ...
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3answers
290 views

Are there any rules of thumb for having some idea of what capacity a NN model needs to have for a given problem?

To give an example. Let's just consider the MNIST dataset of handwritten digits. Here are some things which might have an impact on the optimum model capacity: There are 10 output classes The inputs ...
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0answers
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Should I restart doing research in artificial intelligence, after 20 years of being away from this field? [closed]

I am seeking some advice. I worked on Artificial Intelligence, Machine Learning, Neural Networks back in the 1990s, published papers, built prototypes all in academia. When I joined the workforce ...
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1answer
510 views

What’s the difference between LSTM and RNN?

What's the difference between LSTM and RNN? I know that RNN is a network layer used in neural networks, but what exactly is an LSTM? Is it also a network layer with the same characteristics?
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2answers
53 views

Are connections genes in a genome ever deleted or just disabled?

When a new node is added, the previous connection is disabled and not removed. Is there any situation in which a connection gene is removed? For example, in the above diagram connection gene with ...
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0answers
22 views

How is the receptive field of a CNN affected by transposed convolution?

When computing receptive field recursively through a CNN, does a transposed convolution affect the receptive field the same way that a convolution does if the kernel and stride is the same?
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0answers
57 views

Using tensor networks as machine learning models

Tensor networks (check this paper for a review) are a numerical method originally introduced in condensed matter physics to model complex quantum systems. Roughly speaking, such systems are described ...
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0answers
24 views

What is the difference between an generalised estimating equation and a recurrent neural network?

What is the difference between a generalised estimating equation (GEE) model and a recurrent neural network (RNN) model, in terms of what these two models are doing? Apart from the differences in the ...
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2answers
45 views

Difference between training accuracy and calculating accuracy with class prediction

I have trained my neural network with a dataset of 11200 images, and its validation accuracy was 96%. I saved my model and load its weights to the same neural network. I chose 738 images of my dataset ...
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0answers
43 views

Can neural network be trained to solve this problem?

I'm working on a problem that given a dataset; where each train example is a binary matrix $X_i$ with dimension $(N_i,D_i)$ (think a training example is a feature matrix) each entry is either 1 or 0. ...
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0answers
44 views

Does a fully convolutional network share the same translation invariance properties we get from networks that use max-pooling?

Does a fully convolutional network share the same translation invariance properties we get from networks that use max-pooling? If not, why do they perform as well as networks which use max-pooling?
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30 views

Semi-supervised: Can I predict the label of purposely unlabelled observations?

Let's say I have a data set with of length N. A small proportion N2 is labeled. Can I remove some labels and then 'reverse' this action with a trained neural network? I could then use the same process ...
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1answer
66 views

Which ANN can solve for y = x * x + b?

I am new to ANN. I am trying out several 'simple' algorithms to see what ANN can (or cannot) be used for and how. I played around with Conv2d once and had it recognize images succesfully. Now I am ...
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1answer
41 views

Reinforcement-learning: grey-scaling vs color of CNN input. Tradeoff?

I'm doing reinforcement learning and have a visual observation as state input for my agent. In the Deepmind Atari paper they greyscale the input image before they input it into the CNN to reduce the ...
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0answers
29 views

How to reduce fluctuation of a neural network?

I've modeled an AlexNet neural network, with 50 epochs and a batch size of 64. I used a stochastic gradient descent optimizer with a learning rate of 0.01. I attached the train and validation loss and ...
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1answer
28 views

What is the difference between TensorFlow's callbacks and early stopping?

What is the difference between TensorFlow's callbacks and early stopping?
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1answer
32 views

Is traditional machine learning obsolete given that neural networks typically outperform them?

I have been coming across visualizations showing that the neural nets tend to perform better as compared to the traditional machine learning algorithms (Linear regression, Log regression, etc.) ...
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1answer
23 views

In neural networks, what does the term depth generally mean?

Is it number of units in a layer number of layers overall complexity of the network (both 1 and 2)
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1answer
44 views

Is this neural network architecture appropriate for CIFAR-10?

I have a CNN architecture for CIFAR-10 dataset which is as follows: Convolutions: 64, 64, pool Fully Connected Layers: 256, 256, 10 Batch size: 60 Optimizer: ...
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0answers
7 views

Finding effect of inputs on output (shapely values)

I've developed a neural network which takes in n inputs returning m outputs. I want to see which inputs contribute most with each output. One idea I had is for all inputs/output combinations, lock ...
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0answers
10 views

What will be the sequence of steps in a human activity recognition model using LSTM?

In the context of these steps detection, tracking, action classification and activity recognition. Which step will be first and further sequence?
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1answer
38 views

In a neural network, can colors be used for neurons in place of floating points and would there be any benefit in doing so?

Firstly, some context. I have been reading and watching videos on the subject for around 3 years, but I am still very much a beginner in machine learning and artificial intelligence. That said, I ...
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0answers
20 views

Is it possible to convert Neural Network code in Python into Matlab code? [closed]

I want to convert the code written in Python into Matlab code. May I know is it possible to do that. Share the available ways or methods to do the conversion. May I know is there any Online ...
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0answers
25 views

What is the use of concatenate layer in CNN?

I am not asking what does concatenate layer does in general in point of mathematical operation. But at feature level, what significance does it provide. Does it helps removing false negatives or does ...
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0answers
17 views

How to encode board before input into the neural net?

Currently I'm working on an educational project (implementation of AlphaZero approach to different types of board games). My biggest concern at the moment is how to encode board before input into the ...
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1answer
44 views

How to solve the problem of variable-sized AST as input for a (convolutional) neural network model?

In my work I have a given source code for a module. From this module I generate an AST, whose size is dependent on the size of the module (e.g. more source code -> bigger AST). I want to train a ...
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1answer
64 views

What is teacher forcing?

In the paper Neural Programmer-Interpreters, the authors use the teacher forcing technique, but what exactly is it?
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0answers
15 views

What models will you suggest to use in Industrial Anomaly Detection and Predictive analysis on live streamed data?

I have been working on industrial data, that is fed live, I want to explore a few models which might suit for this the best. The data are KPI data from the manufacturing Industry.
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1answer
51 views

Should I prefer the model with the lowest validation loss or the highest validation accuracy to deploy?

I trained a ResNet20 on Cifar10 and obtained the following learning curves. From the figures, I see at epoch 52, my validation loss is 0.323 (the lowest), and my validation accuracy is 89.7%. On the ...
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1answer
39 views

How does batch size affect model size?

I'm suffering from a significant brain fart while trying to get my head around how does batch size affect overall model size e.g for CNNs. Does it serve as an additional dimension for all the weight ...
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1answer
33 views

Hand-Signs Recognition using Deep Learning Convolutional Neural Networks

I am developing a CNN model to recognize 24 hand-signs of American Sign Language. I have 2500 Images/hand-sign. The data split is: Training = 1250 Images/hand-sign Validation = 625 Images/hand-sign ...
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1answer
47 views

Are there names for neural networks with a well-defined layer or neuron characteristics?

Are there names for neural networks with a well-defined layer or neuron characteristics? For example, a matrix that has the same number of rows and columns is called a square matrix. Is there an ...
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0answers
15 views

Sign Language to Speech conversion

Is there any solution about sign language to speech conversion for mobiles? Can anyone suggest me the flow and tools so that I may implement the solution for mobiles?
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0answers
14 views

Image-to-Image Regression for GO territory classification

I'm trying to implement a neural network that is able to generate an image indicating territory occupation given a board state for GO (a strategy board game). Input images are 19x19x1 grayscale images,...
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1answer
94 views

Is a non-linear activation function needed if we perform max-pooling after the convolution layer?

Is there any need to use a non-linear activation function (ReLU, LeakyReLU, Sigmoid, etc.) if the result of the convolution layer is passed through the sliding window max function, like max-pooling, ...
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0answers
27 views

Can we use GPT-2 to smooth out / correct text?

Are we able to use models like GPT-2 to smooth out/correct text? For instance if I have two paragraphs that need some text to make the transition easier to read, could this text be generated? And, ...
3
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1answer
76 views

Is the LSTM component a neuron or a layer?

Given the standard illustrative feed-forward neural net model, with the dots as neurons and the lines as neuron-to-neuron connection, what part is the (unfold) LSTM cell (see picture)? Is it a neuron (...
2
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1answer
29 views

How are newer weight initialization techniques better than zero or random initialization?

How do newer weight initialization techniques (He, Xavier, etc) improve results over zero or random initialization of weights in a neural network? Is there any mathematical evidence behind this?
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2answers
28 views

Strategy of using intermediate layers of a neural network as features?

There is a popular strategy of using a neural network trained on one task to produce features for another related task by "chopping off" the top of the network and sewing the bottom onto some other ...
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0answers
19 views

Neural network seems to just figure out the probability of a specific result

I am really new to neural networks, so i was following along with a video series, created by '3blue1brown' on youtube. I created an implementation of the network he explained in c++. I am attempting ...
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0answers
23 views

Web stream requests prediction architecture

What's in your opinion the best possible architecture for the following problem ? If you have any code that can be used it would be great . Dataset : 400.000 samples given in hex format in an .xlsx ...
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2answers
222 views

How to estimate the capacity of a neural network?

Is it possible to estimate the capacity of a neural network model? If so, what are the techniques involved?
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1answer
24 views

Interpolating image to increase resolution before feeding it to a neural network

Interpolation is a common way to make an image fit the right input shape for a neural network. But is there any point in using interpolation to make it easier for the network to learn? I assume ...
4
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1answer
53 views

Is there a reason to choose regular momentum over Nesterov momentum for neural networks?

I've been reading about Nesterov momentum from here and it seems like a nice improvement over regular momentum with no extra cost whatsoever. However, is this really the case? Are there instances ...

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