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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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It is possible to use deep learning to give approximate solutions to NP-hard graph theory problems?

It is possible to use deep learning to give approximate solutions to NP-hard graph theory problems? If we take, for example, the travelling salesman problem (or the dominating set problem). Let's say ...
Jake B.'s user avatar
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6 votes
1 answer
172 views

How to graphically represent a RNN architecture implemented in Keras?

I'm trying to create a simple blogpost on RNNs, that should give a better insight into how they work in Keras. Let's say: ...
Mindaugas Bernatavičius's user avatar
4 votes
0 answers
131 views

Could zero-padding affect learning in a negative way?

I implemented an LSTM with Keras to perform word ordering task (given a syntactically unordered sentence, the goal is to label ...
pairon's user avatar
  • 143
4 votes
0 answers
359 views

What are the ways to calculate the error rate of a deep Convolutional Neural Network, when the network produces different results using the same data?

I am new to the object recognition community. Here I am asking about the broadly accepted ways to calculate the error rate of a deep CNN when the network produces different results using the same data....
Daqi Dong's user avatar
3 votes
1 answer
747 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 ...
Dawid's user avatar
  • 131
3 votes
0 answers
65 views

Deep Q-Learning agent poor performing actions. Need help optimizing

I'm trying to make deep q-learning agent from https://keon.io/deep-q-learning My environment looks like this: https://i.sstatic.net/EJHTD.jpg As you can see my agent is a circle and there is one ...
EnesZ's user avatar
  • 131
3 votes
0 answers
39 views

Does it make sense to add word embeddings as additional features for LSTM model?

I have an LSTM model. This model takes as input tokens. Those tokens represent XML markups extracted from some XML files. My model is working fine. However, I want to optimize it by adding word ...
Emna Jaoua's user avatar
3 votes
1 answer
748 views

Binary mode or Multi-label mode is correct when using binary crossentropy and sigmoid output function on multi-label classification

I would like to ask a question about the relationship of accuracy with the loss function. My experiment is a multiclass text classification problem, and I have built a Keras neural network to tackle ...
NikSp's user avatar
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2 votes
0 answers
39 views
+100

How to Create a Neural Network Model to Generate Dance Movements Based on Music in MMD Format

I am working on a project where I need to create a neural network model to generate dance movements based on music. My goal is to achieve results similar to this video: https://youtu.be/FrA7f5F9TsI ...
meow meow's user avatar
2 votes
0 answers
179 views

Why use z_mean to plot the latent space learned by a Variational Autoencoder?

In the Keras website, there is an example code of a Variational Autoencoder. At the end of such a page, there is an example code that plots the latent space learned from MNIST. The code is as follows: ...
AlexSC's user avatar
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2 votes
0 answers
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Single-value loss/training in a CNN with a tensor output

I am playing around with an idea of using using Q-learning with a DQN (Deep Q-Network), to determine the optimal position of a number of 'units' on a grid of allowed locations, according to some ...
Anders BB's user avatar
2 votes
0 answers
41 views

Why does the loss stops reducing after a point in this Transformer Model?

Context I was making a Transformer Model to convert English Sentences to German Sentences. But the loss stops reducing after some time. Code ...
NITIN AGARWAL's user avatar
2 votes
0 answers
52 views

Loss function decays linearly in segmentation MRI fascia

I am working on a segmentation of MRI images of the thigh. I am trying to segment the fascia, there is a slight imbalance between the background and the mask. I have about 1400 images from 30 patients ...
Lis Louise's user avatar
2 votes
0 answers
196 views

Inaccurate masks with Mask-RCNN: Stairs effect and sudden stops

I've been using matterport's Mask R-CNN to train on a custom dataset. However, there seem to be some parameters that i failed to correctly define because on practically all of the images, the bottom ...
Nawra C's user avatar
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2 votes
2 answers
79 views

Heavily mixing signal differentiation from Open Set of backgrounds via CNN

I am currently attempting to detect a signal from background noise. The signal is pretty well known but the background has a lot of variability. I've since come to know this problem as Open Set ...
Mecho Engineer's user avatar
2 votes
2 answers
564 views

How can I use autoencoders to analyze patterns and classify them?

I generated a bunch of simulation data from a complex physical simulation that spits out patterns. I am trying to apply unsupervised learning to analyze the patterns and ideally classify them into ...
Pavan Inguva's user avatar
2 votes
1 answer
143 views

Is my fine-tuned model learning anything at all?

I am practicing with Resnet50 fine-tuning for a binary classification task. Here is my code snippet. ...
bit_scientist's user avatar
2 votes
0 answers
32 views

How are batch statistics computed in Recurrent Batch Normalization?

I'm implementing recurrent BN per this paper in Keras, but looking at it and those citing it, a detail remains unclear to me: how are batch statistics computed? Authors omit explicit clarification, ...
OverLordGoldDragon's user avatar
2 votes
1 answer
83 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 ...
PMu's user avatar
  • 21
2 votes
1 answer
267 views

How to represent integer values in sequence to sequence prediction task in encoder-decoder LSTM?

I have a large 2D grid having 30k rows and 35k columns, so a total of 30x35k grid cells. Each grid cell is represented by a unique integer number (identity of grid cell). I have several trajectories ...
Asif Khan's user avatar
  • 181
2 votes
0 answers
56 views

Which deep neural networks are appropriate for the detection of bombs?

This is a follow-up question from my previous post here about explosion detection. I gathered a dataset of explosions. As I'm new to Deep Learning in Keras, I'm trying to see what architecture best ...
Mary's user avatar
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2 votes
0 answers
283 views

how to use Softmax action selection algorithm in atari-like game

I'm currently writing a program using keras (python 3) to play a game similar to Atari games, only in this one there are objects moving in the screen in different angles and directions (in most of ...
E. Ginzburg's user avatar
2 votes
0 answers
170 views

What are the possible neural network architecture for linear regression or time series regression?

I started modeling a linear regression problem using dense layers (layers.dense), which works fine. I am really excited, and now I am trying to model a time series linear regression problem using CNN, ...
Jun Liu's user avatar
  • 29
2 votes
0 answers
206 views

Understanding CNN+LSTM concept with attention and need help

I have a question about the context of CNN and LSTM. I have trained a CNN network for image classification. However, I would like to combine it with LSTM for visualizing the attention weights. So, I ...
Joker's user avatar
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2 votes
0 answers
209 views

Paper & code for "unsupervised domain adaptation" for regression task

Does anyone know a paper or code that does "unsupervised domain adaptation" for regression task? I saw most of the papers were benchmarked on classification tasks, not regression. I want to do ...
offchan's user avatar
  • 325
2 votes
0 answers
27 views

In addition to matrix algebra, can GPU's also handle the various Kernel functions for Neural Networks?

I've read a number of articles on how GPUs can speed up matrix algebra calculations, but I'm wondering how calculations are performed when one uses various kernel functions in a neural network. If ...
Greg Thatcher's user avatar
2 votes
0 answers
47 views

Difference between retraining on different portions of data and training initially on larger data set

I have a large data set that doesn't fit in memory and would have to use something like Keras's model.fit_generator if I would like to train the model on all of the ...
Георги Кременлиев's user avatar
2 votes
0 answers
167 views

Mapping Actions to the Output Layer in Keras Model for a Board Game

I have created a game based on this game here. I am attempting to use Deep Q Learning to do this, and this is my first foray into Neural networks (please be gentle!!) I am trying to create a NN that ...
pi-r-squared's user avatar
2 votes
0 answers
606 views

Mountain car problem with images - not converging

I'm trying to find the optimal policy for the mountain car problem using deep Q learning with images as input, however, I cannot find a way to get my Q function to give me good solutions (I followed ...
user3548298's user avatar
2 votes
1 answer
944 views

Periodic Pattern in Validation Loss Curve

I am currently trying to solve a regression problem using neural networks. I want to detect movement patterns in images over time (video) and output a continuous value. During the training process I ...
Unknown User's user avatar
2 votes
0 answers
502 views

Deep NN architecture for predicting a matrix from two matrices

Recently my friend asked me a question: having two input matrices X and Y (each size NxD) where D >> N, and ground truth matrix Z of size DxD, what deep architecture shall I use to learn a deep model ...
vaxherra's user avatar
2 votes
0 answers
485 views

CNN attention maps on non-images

My datasets are not actual images, so using methods with ImageDataGenerator or pre-trained networks might not apply in this case. Data Structure: Each "image" is a 2048-long vector that has float ...
rajkarthikkumar's user avatar
1 vote
0 answers
37 views

Loss Function for Binary Classification with Multiple Correct Choices

I have a binary classification problem, where there are multiple correct predictions, however, I would consider the prediction to be correct if the highest confidence prediction of a 1 is correct. I ...
John Meighan's user avatar
1 vote
1 answer
2k views

keras model accuracy not improving

I am trying to do multi class(16) classification, however no matter what parameters or number of layers I use my accuracy is not improving, its in 30s the max I got was 43. I have tried early stopping ...
SACHI SINGH's user avatar
1 vote
1 answer
150 views

What could cause the hamming loss and subset accuracy to get stuck in a multi-label image classification problem?

I am rather new to deep learning and got some questions on performing a multi-label image classification task with keras convolutional neural networks. Those are mainly referring to evaluating keras ...
Phil's user avatar
  • 11
1 vote
0 answers
872 views

What would be the advantage of making channel dimension first in TensorFlow Keras implementation?

I was reproducing the findings of a research article in which I discovered that they had switched the Channel dimension from last to first. To clarify this concept, I went through A Gentle ...
Nafees Ahmed's user avatar
1 vote
0 answers
130 views

Would the reward normalization be wrong in early episodes?

It's confusing me that how can we normalize the reward without actually knowing the true mean and variance of the reward distribution, specifically, at the early steps and episodes. This may cause ...
fardis nadimi's user avatar
1 vote
0 answers
23 views

Neural Network Regression Experiment Going Wrong

I've been trying to get a simple regression experiment going with a neural network and I would like some help interpreting what is going wrong. My goal is to see what level of regression accuracy I ...
jared-nelsen's user avatar
1 vote
0 answers
68 views

Pixel values of segmap in multi-class semantic segmentation

I'm preparing a dataset for a multiclass semantic segmentation using U-Net like architecture. To be precise, I've got it ready but a question came to my mind. How does pixel values of a segmentation ...
Nuwanda's user avatar
  • 11
1 vote
0 answers
135 views

Is a true RNN auto encoder possible with Keras/TF

I want to get some encodings for temporal data (with a highly varying number of timesteps). The dataset is of the format: ...
Tobi Akinyemi's user avatar
1 vote
0 answers
108 views

Does the order of data augmentation and normalization matter?

What is the preferred order of data augmentation and normalization? Is it the former followed by the latter?
shyam vishnu's user avatar
1 vote
0 answers
71 views

Can I constrain my neurons in a neural network in according to the orders of the input?

I'm working with data that is ranked. So the inputs are 1,2,3 etc. This means the smaller numbers (ranks) are preferred to the larger ones. Hence the order is important. I want to estimate a number ...
Gergő Barta's user avatar
1 vote
0 answers
362 views

How to deal with KerasRL DDPG algorithm getting stuck in a local optima?

I am using KerasRL DDPG to try to learn a policy on my own custom environment, but the agent is stuck in a local optima although I am adding the OrnsteinUhlenbeck randomization process. I used the ...
BAKYAC's user avatar
  • 36
1 vote
0 answers
361 views

DQN Agent with a 2D matrix as input in Keras

I have a Reinforcement Learning environment where the state is a 2D matrix with 0s and 1s (only one column with the value of 1 in each row). Example: ...
Ness's user avatar
  • 206
1 vote
0 answers
158 views

How to design my Neural Network for Game AI

For my school project, I have to develop an agent to play my game. The base I have is a 'GameManager' which call 2 AIs, each taking a random move to do. To make my AI perform, I decided to make a ...
Benjamin Darras's user avatar
1 vote
0 answers
208 views

Keras model accuracy not improving beyond threshold

I am currently working on a public project for the National Weather Model. We are experimenting with using a recurrent neural network to replace the output of a quadratic formula that is in use. The ...
Jacob Hreha - NOAA Affiliate's user avatar
1 vote
0 answers
153 views

What is the best way to make a deep reinforcement learning environment with a continuous 2D action space?

I understand that the actor-critic method is probably where I want to start because of how it works with continuous action spaces. However, the problem I am trying to solve would require the action be ...
Dale Larie's user avatar
1 vote
0 answers
125 views

Embedding Layer into Convolution Layer

I'm looking to encode PDF documents for deep learning such that an image representation of the PDF refers to word embeddings instead of graphic data So I've indexed a relatively small vocabulary (88 ...
NewEndian's user avatar
  • 131
1 vote
0 answers
89 views

How much data do we need for making a successful de-noising auto-encoder?

Is there a guide how much data do you need for making successful denoising model using autoencoders? Or the rule is, the more data, the better it is? I tried with small dataset 350 samples, to see ...
Vesko Vujovic's user avatar
1 vote
0 answers
41 views

Is using a filter of size (1, x, y) on a 3D convolutional layer the same as using a filter of size (x,y) on a 2D convolutional layer?

I'm trying to predict some properties of videos with Keras using the following rough architecture: Feed each frame through the same 2-D convolutional layer. Take the outputs of this 2-D ...
J. Pistachio's user avatar