Questions tagged [tensorflow]

A Python library for deep learning developed by Google. Use this tag for any on-topic question that (a) involves tensorflow either as a critical part of the question or expected answer, & (b) is not just about how to use tensorflow.

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34 views

Confusion with Computing Probabilities of a Normal Distribution without the Integral

How does this code is calculating the probability of Normal distribution without calculating the integral ...
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1answer
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Why is binary cross entropy (or log loss) used in autoencoders for non-binary data

I am working on an autoencoder for non-binary data ranging in [0,1] and while I was exploring existing solutions I noticed that many people (e.g., the keras ...
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How to predict similarity of unseen data to the training set?

I have a time series of human pose data which are recorded from real humans. I want to train the model with unsupervised learning on the training data. Let's call this the "real" training data. The ...
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1answer
2k views

Parameters Grid Search for Keras LSTM on Time Series

How do you do grid search for Keras LSTM on time series? I have seen various possible solutions, some recommend to do it manually with for loops, some say to use scikit-learn GridSearchCV. Feedback ...
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1answer
213 views

High AUC and Accuracy but weird output in confusion matrix

I am working on image classification problem to determine gender given a face. The dataset is located here gender face dataset on kaggle (link to my notebook). The class distribution is as follows. <...
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1answer
18 views

Tensorflow choice of values of variables after training [closed]

I am trying to build a neural network, that is able to perform a linear regression. After for example 1000 epochs, I encountered the situation, where the smallest loss-value was not the last loss-...
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1answer
1k views

Loss during minibatch gradient descent

I have minibatch gradient descent code in Tensorflow for function approximation, but I am unsure when to calculate the loss. First, I create batches for x and y data. Then, I shuffle both these ...
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1answer
87 views

Is this Tensorflow bias vector shaped correctly?

In the text I read the following: I’m confused on the dimensions of the bias vector. How can we add a(m,1) vector to a(1, p) ...
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40 views

CTC classification for License Plate with two lines

I have gone through this tutorial and have understanding how CTC works for end to end text recognition. But for recognition of images with texts in two lines Would it be able to use CTC for ...
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30 views

ML Regressor model performance conclusion RSME vs STD DEV

Perhaps my question is still slightly silly but apparently even though lot of folks talk about how to evaluate the rightness of your model there still blur the right evaluation procedure at least for ...
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1answer
511 views

What is the initial state of the tf.contrib.rnn.LSTMCell? [closed]

Does tf.contrib.rnn.LSTMCell assign itself an initial state of zeros or is it random for each batch or per complete run through (if I run the model twice will it have the same initial state both the ...
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193 views

Implementing WARP loss in tensorflow [closed]

I notice there are attempts to implement WARP loss in Keras such as (https://stackoverflow.com/questions/46299554/implimentation-of-warp-loss-in-keras) But I have not seen any githubs or publications ...
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54 views

Tensorflow InvalidArgumentError: The determinant is not finite [closed]

I'm trying to fit a Mixture of Gaussians to a data set. First the data is clustered using K-Means Clustering. Each cluster is then fitted with a Gaussian.To avoid inversion of large covariance matrix, ...
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1answer
300 views

How to reconstruct negative acceleration values using a simple autoencoder?

I am trying to reconstruct the acceleration values of a tri-axial accelerometer using a simple autoencoder. As acceleration values are often negative (e.g, -3.4) therefore using a ReLU activation ...
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Training on cifar100 [duplicate]

I am building a model on training a cifar100 images I try to follow others work on training cifar10 and they work very well(around 90% accuracy), so I add some more layers for training cifar100.But ...
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4answers
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Is it possible to give variable sized images as input to a convolutional neural network?

Can we give images with variable size as input to a convolutional neural network for object detection? If possible, how can we do that? But if we try to crop the image, we will be loosing some ...
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1answer
597 views

forget_bias interpretation in tensorflow

In Basic LSTM cell of tensorflow there is an argument named forget_bias. From the documentation of ...
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1answer
444 views

Understanding TensorFlow' conv2d for multiple output channels

I'm trying to understand the convolution process better by applying conv2d to different inputs. However I get unexpected result by transforming 3x3 matrix from 1 to ...
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1answer
3k views

What does decay_steps mean in Tensorflow tf.train.exponential_decay?

I am trying to implement an exponential learning rate decay with the Adam optimizer for a LSTM. I do not want the 'staircase = true' version. The decay_steps for me feels like the number of steps that ...
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2answers
99 views

Keras model optimization of 2D arrays

I am trying to train a CNN with 2D arrays of normalized numbers. Example of 2D training array: ...
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1answer
27 views

Why the bias distribution in the last layer is always close to symmetric?

I am trying to train a very simple model, the first layer is full connection, while the output layer output 2 values to represent different categories. ...
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1answer
103 views

sample data for training neural networks for self-driving cars [closed]

If I ask the question in the wrong forum, let me know, I will delete it. I want see sample data for training neural networks for self-driving cars. I understand that there will be geodata and image ...
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2answers
221 views

Is it reasonable to use VGG16 with a new fully-connected layer for binary image segmentation?

I am working on binary image segmentation of traffic signs (of which I have RGB images of size 224x224 and accompanying grayscale masks) where I want to classify each pixel as either part of a traffic ...
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1answer
244 views

Emotion detection: neural network overfitting on audio files

I am working on an analysis of audio data to understand emotions using the RAVDESS dataset. The input is the Mel-frequency cepstral coefficients (MFCCs) of each audio file, extracted using a Python ...
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1answer
435 views

Tensorflow batch normalization for images - padding issue

I'm trying to train anomaly/defect detection network on custom images. Let say I have to detect scratches on special steel boxes and I have two views: side view with dimension 2300 x 550 (width x ...
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162 views

Neural Network Parallel Architecture

I am a beginner to Machine Learning. While working on a personal project with VAEs, I had an idea. I will first give some background. Sometimes I have seen that it is common practice, when creating ...
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2answers
98 views

Deep Neural Network visualization on multi dimension datasets [closed]

I have seen the PlayGround of Tensorflow. But it is using only 2D values which means only 2 inputs are taken. I have 7 inputs and the output is only 1. See the datasets sample: ...
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1answer
63 views

I don't understand such a difference in the accuracy, please help

When I use a normalized values for the values of the target column in the following DL regression model I get a very good accuracy, and if I don't, the accuracy is a mess. However I've reading that ...
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51 views

Visualizations not appearing in Tensorflow-PyCharm IDE [closed]

I am using PyCharm Community Edition and Python 3.7. Via Anaconda, I have installed the Tensorflow machine learning package. I am following the regression tutorial here, but I am getting limited ...
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1answer
110 views

Object detection training: will mirroring images help or hinder?

Will Tensorflow training benefit from doubling the images by mirroring images (flipping horizontally)? In other words, if the original image contains text that says: "this is a test", the mirrored ...
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Why does the Conv Neural Net using Tensorflow returns same predictions for all the data points [duplicate]

I am predicting usage quantity for different customers across different categories. Following is the network architecture. ...
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0answers
624 views

Auxiliary loss function keras

I'm trying to write the custom loss function called ( Auxiliary loss function) which are two softmax loss functions put together that controls both the Context path and Spatial path of the network. ...
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138 views

Forming Conditional Probabilities in tensorflow

This is a repost from stack, but I think it may be more applicable here. Granted there is even a bounty for it there, if someone could answer it. https://stackoverflow.com/questions/53421179/forming-...
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1answer
217 views

Question about bounding boxes to handle false positives

I have trained a model to detect vehicle number plates. The issue is that it returns matches of partial plates, with high confidence. To eliminate partials I want to add two new boxes to the images ...
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1answer
264 views

Entropy of a Gaussian Process: Log(Determinant(CovarianceMatrix)) [closed]

I want to be able to compute the entropy of a Gaussian Process. To that end, I have a simple example in GPFLow. I have a latent function which I sample with two different levels of noise, L1 and L2 ...
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2answers
723 views

How to train a stock trading neural network so that the 'profit' parameter is maximized?

I am watching some beginner level video training on neural networks using Tensorflow / Keras to get a better understanding of how they work and how to best implement them. I have some questions on ...
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1answer
237 views

Implementation of WAE-GAN does not match with the description in the paper

According to the litterature and specifically to this paper, the wasserstein autoencoders is an encoder-decoder architecture. So it must contain encoder and decoder parts. in the algorithm ...
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1answer
669 views

RMSprop difference rho and decay in Tensorflow

As this post showed nicely, there is a difference between rho and the decay in RMSprop. I can't clearly see what tensorflows RMSprop parameter decays stands for. Is this the learning rate decay? And ...
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1answer
433 views

How to cluster parts of broken line made of points?

I am studying clustering techniques and i am pretty new at this topic. Here is my problem: I created a 5 lines which are made of points. This lines are supposed to be continuous and they look like ...
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0answers
156 views

Recognition the same object from different views

I have 33 classes (33 different objects). I need to recognize the object from any view of the object. Like a packet of potato chips, the packet has different appearance from different view (as shown ...
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0answers
39 views

Feature ranking for ANN

I am doing a regression analysis on 1 hidden layer feed forward NN and have 18 input features with 1 output. I Intend to do some feature ranking so it can give me an idea of the most important to the ...
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1answer
3k views

How to deal with really sparse time series data for a binary classification task using RNN or LSTM?

I have a binary classification prediction task and more often than not, the time series data is like really sparse. The number of zeroes in the time series data is almost always more than 99%. I ...
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0answers
52 views

A mistake in Tensorflow's documation?

Tensorflow's documentation gives an example for text generation using a RNN with eager execution. To the best of my understanding, this examples defines a simple RNN (with a GRU cell and a projection ...
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1answer
45 views

Do two TensorFlow models on different python files conflict? [closed]

I have a TensorFlow model that in each training episode I need to run a function on the data in that episode. This function is also a TensorFlow model in another python file that I import to the main ...
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105 views

How does the internal state of Tensorflow's “dtf.nn.dynamic_rnn()” change?

I am trying to do a uni-variate forecasting and I have come across this question quite a lot. This question is regarding TensorFlow's "dtf.nn.dynamic_rnn()". NOTE: When I say internal state I am ...
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0answers
49 views

Why normalize when all features are on the same scale? [duplicate]

So I'm doing the tensorflow tutorial found here: https://www.tensorflow.org/tutorials/keras/basic_classification Basically, my input is a [28x28] matrix (image) that I flatten to a [1x784] vector. ...
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1answer
467 views

Neural networks to predict a nonlinear curve

I want to model a complex nonlinear function using neural networks (keras). Training data: input - 8500 x 176 matrix of features, output - 8500 x 8 matrix, each row corresponds to 8 points which ...
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1answer
317 views

What is the purpose or benefits of fully connected layer at the middle of Convolutional Network?

Is there any benefits to have FC layer at the middle of CNN network? For example, in this network, FC7 has kernel size is 1. What is the benefits of using kernel size 1 in this use? Those inception ...
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1answer
489 views

How to get validation accuracy in neural network training?

The following plot shows over fitting in training using training accuracy and validation accuracy during training. How to get that plot in training? My understanding is that we have training set and ...

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