Questions tagged [keras]

For questions related to Keras, the modular neural networks library written in Python. However, note that programming questions are off-topic here.

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43 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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102 views

Does this tutorial use normalization the right way?

There is this video on pythonprogramming.net that trains a network on the MNIST handwriting dataset. At ~9:15, the author explains that the data should be normalized. The normalization is done with ...
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Generation of realistic real-valued sequences using Wasserstein GAN fails

My goal is to generate artificial sequences of real-valued data (e.g. time series) with GANs. Starting simple I tried to generate realistic sine-waves using a Wasserstein GAN. But even on this simple ...
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13 views

How do I build a multi RNN network with keras?

I have 2 (independently long) sequences (a and b) of feature vectors that I want to use as input for a neural network. The idea was to build 2 GRU based encoders (one for each sequence). I would than ...
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28 views

How to use Before / After images to train a model

I am trying to create a model that can clean pictures of noise, blur, high luminosity etc, but I do not know how to do that. I have tried to search for it a lot, and I couldn't find anything that ...
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30 views

Reversing A Keras Dense GAN

I have a Keras GAN where every layer in the generator has more neurons than the last and also where they all have an activation of LeakyReLU(alpha=0.1). I am trying to map the image back to the noise ...
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339 views

Reasoning behind $Zero$ validation accuracy in the following ResNet50 model for classification

I have written this code to classify Cats and dogs using Resnet50. Actually while studying I came to the conclusion that Transfer learning gives very good accuracy for deep learning models, but I ...
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54 views

not sure if fine-tuned network is finely-tuned

I am practicing with Resnet50 fine tuning for binary classification task, here is my code snippet. ...
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35 views

Can anyone explain the pixelwise accuracy metric used in this paper? Also a question to the KL Divergence Loss

So I am making a project based on this paper: https://arxiv.org/ftp/arxiv/papers/1901/1901.07761.pdf In this paper, a U-Net is used to generate optimized mechanical structures. I am trying to ...
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29 views

How to handle a high dimensional video (large number of frames per video) data for training a video classification network

I have a video dataset as follows. Dataset size: 1k videos Frames per video: 4k (average) and 8k (maximum) Labels: Each video has one label. So the size of my input will be (N, 8000, 64, 64, 3) ...
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40 views

What is the correct input shape for my LSTM network?

My professor gave us a workshop where we have to do classification of a dataset of ECG signals between healthy and unhealthy types using LSTM. Each signal consists of 1,285 time steps. What my prof ...
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1answer
32 views

Is CNN capable of extracting the descriptive statistics features

I was trying to build a CNN model. I used time series data of daily temperature to predict if there is risk of an event, say bacteria growth. I calculated the descriptive statistics of the time series,...
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28 views

Does a varying ANN model accuracy mean underfitting or overfitting?

Background: This is for a simulated robot with four legs, walking on a flat terrain. The ANN (an MLP) is given inputs as the robot's body angle, positions and angle of each leg with respect to the ...
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26 views

Applying Machine Learning to 2D Laser Scanner Data

We are using 2D Laser Scanner to scan various objects of different geometric shapes for e.g. cylinder, spiked, cylinder with notch, cylinder with curved edges e.t.c. The dataset contains points in the ...
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38 views

How to perform regression with multiple numeric (positive and negative) inputs and one numeric output?

I have a dataset with different types of numerical values (both negative and positive numerical values) for the inputs (for example, -40, -35, 1, 25, 39, etc., that is, multiple inputs) and single ...
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21 views

Keras correlation coefficient as network metric in R

does anyone know how to use the correlation coefficient or squared correlation coefficient as a metric in keras in R (although other languages may provide clues). This is for a CNN that functions ...
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29 views

How to change the architecture of my simple sequential model

I'm new to Deep Learning with Keras. With some tutorials online for cat vs non-cat classification, I was able to compile this simple architecture for my own ...
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27 views

How to implement CNN with variable number of images in tensorflow or keras?

Suppose I have a problem where I want to classify the color of LEDs seen in the image. I can use OpenCV to pinpoint the exact location of these LEDs but I do not know their color for sure because the ...
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99 views

Which model can I use for this problem with multiple inputs and outputs?

Which model is the most appropriate for this problem with multiple inputs and outputs? The data set is A1, A2, A3, A4, A5, A6, B1, B2, B3, B4 where ...
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27 views

How to get same accuracy with identical models in Keras and Tensorflow?

As we all know Keras backend uses Tensorflow and so it should give out same kind of results when we provide same parameters, hyper-parameters, weights and biases initialisation at each layer, but ...
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16 views

Make an LSTM model for each class separately

I have a dataset of some activities. The dataset contains the status of different sensors and the label of activity. T trained a model in Keras with the following architecture which models the ...
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2answers
132 views

How to train a LSTM model with multi dimensional data

I am trying to train my model using LTSM layer in Keras (python). I have some problems regarding the data representation and feeding it into the model. My data is 184 XY coodinates encoded as a numpy ...
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59 views

Can I perform image recognition using a very small dataset?

I have 3 types of classes and I have 2 images of each object (or class). Can I perform image recognition using this very small dataset?
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67 views

Why doesnt my lstm model for time series prediction improve after certain level of performance?

I created an lstm model which predicts multioutput sequeances. It takes variable length sequences as input. These sequences are padded with zero to obtain equal length. Note that the time series are ...
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67 views

Keras CRNN implementation with multiple input images

Hello I am trying to implement a CRNN with multiple input images (in my context it is 6 images) This is a regression problem and output is two real value. And for the CNN block I am thinking of using ...
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31 views

Why such a big difference in number between training error and validation error?

Question Why such a big difference between my 'Train loss' and 'Validation loss' as shown in the picture below? Is it a signal that my codes are wrong and my trained network is wrong as well? Some ...
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51 views

How can I interpret the following error graph?

I am training a neural network which produces the following errors (epoch number on the x axis). I have some questions regrading interpreting it. When I say ...
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67 views

Simple weakly supervised Object localizetion using keras. How to visualize the results?

I am following this link : Weakly-supervised-object-localization to create heatmap of the region in an image where the CNN looks to identify the class. As per the above mentioned repository , ...
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188 views

Policy gradient loss for neural network training

Say i want to train a neural network with 10 classes as outputs and use categorical_cross_entropy as a loss function in keras. This will try to fit the training ...
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42 views

how to add the pool4 to the 2 x conv7 in FCN-16s using keras?

Now I'm using tensorflow.keras to implement the FCN-16s, this picture may be different with others, you should focus this it add ...
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142 views

How can VAE have near perfect reconstruction but still output junk when using random noise input

I am creating a VAE for time series data using CNNs. The data has 4800 timesteps and 4 features. It is standardized and normalized. The network I am using is implemented in Keras as follows. I have ...
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27 views

Kera's (normal) LSTM uses the GPU?

I'm running Kera's LSTM (not CuDNNLSTM) but I notice my GPU is under load. I need recurrent dropout, so I can only stick with <...
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36 views

how to estimate which item is bought most using AI

Problem: Maintaining the products is a big task for a retailer. If we can estimate using AI to predict which products will sell the most, we can maintain sufficient stocks of the product without ...
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1k 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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29 views

Sequence to sequence machine learning / NMT - converting numbers into words

I want to do some sequence to sequence modelling on source data that looks like this: /-0.013428/-0.124969/-0.13435/0.008087/-0.269241/-0.36849/ with target data ...
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236 views

How To Improve This Sentiment Analysis Model

A.I Community, this is my first post on here I am currently reading, learning and designing models. At the moment I'm working on this sentiment analysis tool; from what I gather sentiment analysis can ...
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130 views

Questions regarding keras activation maximization visualization

I wanted to use the visualization of the activation maximization of the filters that is described in the following keras tutorial/blog: https://blog.keras.io/how-convolutional-neural-networks-see-the-...
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347 views

How does backpropagation work on a custom loss function whose components have magnitudes of different orders?

I want to use a custom loss function which is a weighted combination of l1 and DSSIM losses. The DSSIM loss is limited between 0 and 0.5 where as the l1 loss can be orders of magnitude greater and is ...
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230 views

Transfer learning from model trained in a similar dataset

I am currently working on a defect detection algorithm but I only have a few samples of defects.I googled for defect detection datasets and I found this one: http://resources.mpi-inf.mpg.de/...
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2answers
64 views

CNN Pooling layers unhelpful when location important?

I'm trying to use a CNN to analyse statistical images. These images are not 'natural' images (cats, dogs, etc) but images generated by visualising a dataset. The idea is that these datasets hopefully ...
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22 views

Pytorch and keras ddqn seem identical, only keras learns

I followed a tutorial for ddqn to beat pong, it beats it with a perfect score in keras, but trying to translate it to pytorch it doesn't learn at all. What am I missing? I pasted all the code for each ...
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25 views

How to make a CNN/RNN on a non-binary dataset?

I am using TensorFlow + Keras to make a CNN/RNN. I'm quite new to AI, I've only made a few relatively basic networks for image regression/classification. The end goal of my project is to determine the ...
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1answer
28 views

How to construct input dependent convolutional filter?

I am constructing a convolutional variational autoencoder for images, starting out with mnist digits. Typically I would specify convolutional layers in the following way: ...
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9 views

What is the difference between TimeDistributed CNN+RNN and passing sequence of features to RNN

I found Keras API that allows to add additional time dimension. ...
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13 views

Why is the variance of my model predictions much smaller than the training data?

I trained a GRU model on some data and then created a bunch of predictions on a test set. The predictions are really bad, as indicated by a near zero R2 score. I notice that the variance of the model ...
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47 views

ConvNet - What to improve regarding architecture, procedure and technique?

I have a dataset of 180k images of license plates (so, not necessary to localize the license plate at first) for which I try to recognize the characters on the images (License plate recognition). All ...
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37 views

Micro average f1_score, None average f1_score cannot increase more than 0.71, 0.50 respectively for the best model estimator

I am training a multilabel text neural network and the model metric I chose, to measure the performance of the training and the validation sets, is the f1 score (Micro average, None average). However, ...
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38 views

CIFAR-10 can't get above 10% Accuracy with MobileNet, VGG16 and ResNet on Keras

I'm trying to train the most popular Models (mobileNet, VGG16, ResNet...) with the CIFAR10-dataset but the accuracy can't get above 9,9%. I want to do that with the completely model (include_top=True) ...
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22 views

Time distributed word position prediction

I am facing the following problem. I need to create a model to predict the product groups from product title. For each word in sentence I need to predict position of a word marked as product. My ...
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22 views

Different result from k-cross validation model and Train-Validation-Test split model ? (AI fresher question)

I am starting to learn about Neural Network and I have come into one problem that I am still learning how to figure it out. I have a dataset with shape (105,96) (105 samples and 95 first column as ...