All Questions
19 questions
1
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0
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11
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Classification of intervals in time series data of multiple instances
I have a problem that I am trying to frame. I have signal data from ECG (a classic signal over time data). A close example here: https://github.com/jjongjjong/ECG_segmentation_1DUnet
I am basically ...
- 125
0
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0
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13
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Question on a paper which talks about stacking several fully connected layers of 2 neural networks
So to preface, my knowledge on neural networks is very limited, and I've had a very difficult time trying to comprehend the details of this paper.
My background is in maths, and I've created a ...
- 101
0
votes
1
answer
230
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Input Tensor Shape for CNN Binary Classification of Time Series Data
I want to predict whether a machine will fail based on the most recent set of measurements taken by on-board sensors. I have several dozen machines, each with a sensor that takes a measurement at ...
- 21
1
vote
1
answer
1k
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Concatenation or separate channels for a CNN
let's say I am classifying time series data from multiple channels in a biomedical setup (e.g. 12 lead ECG).
I have been reading this paper on a CNN-based (ResNet) architecture for assesing the ...
- 111
7
votes
1
answer
10k
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Why CNN is suitable for time-series data?
I am confused by the statements that I came across in two different papers.
The statement from the paper titled as "Detecting Cyber Attacks in Industrial Control Systems Using Convolutional ...
- 325
0
votes
1
answer
98
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Predicting what a user might eat next given a history of food logs
I'm trying to predict what a user might eat next give history of a user's food logs and a users demographic data.
The data that I have for each user is:
Food logs (Where users track what foods they ...
- 101
2
votes
1
answer
617
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Time series classification using 1D-CNN with different-length input
I work on one-dimensional (1-D) time series classification using 1D-CNN. But the length of the time series data is variant, e.g., from 80 to 120. So it's hard to specify the size of input layer of CNN ...
- 21
0
votes
0
answers
96
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Preventing certain weights from going to 0
I would like to use a convolutional neural network to study a time series data set. I have experimental measurements taken at three different time intervals. With this I plan to create an input that ...
- 113
1
vote
1
answer
2k
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CNN architecture for 1D time series classification
I would like to use a CNN in order to classify signal data consisting of min. 500 data points into 3 categories. What kind of architecture and design considerations do I need to take into account and ...
- 63
1
vote
1
answer
264
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Is there a ML model that can determine the sequence that leads to an outcome?
I have a problem where a certain sequence of events leads to a certain outcome. The problem is, I am not sure exactly what the sequence is. I am hoping to get some possible sequences to test as ...
- 3,263
1
vote
0
answers
176
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autoencoding spiky time series - better loss function?
I am experimenting with convolutional autoencoders for time series. My first network architectures work quite well. However, the autoencoder has a tendency to soften the spikes in the time series. And ...
- 253
3
votes
1
answer
3k
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Forecasting Sharp Peaks in a Time Series using Convolutional Neural Networks
I am having with me a time series data. Occurrences of sharp peaks in the variable value can possibly mean the onset of an undesired event.
We thought of using a deep convolutional neural network to ...
- 165
0
votes
1
answer
2k
views
Higher value of strides in conv1d
I am using Conv1d for time-series data and I have create a model as follows,
...
- 15
2
votes
2
answers
4k
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1D CNN for time series regression without pooling layers?
I am working on a prognostics task, where I predict the Remaining Useful Life of some equipment (i.e.: time steps remaining until failure). In order to do that, I use multivariate time series sensor ...
- 121
2
votes
0
answers
644
views
Time-series predictions constant offset from reference values
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 for different medical indices.
...
- 121
1
vote
0
answers
2k
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Time-Series Prediction with Convolutional Neural Networks (CNN) Input Data Shape Problem and How To Choose Xtrain YTrain
I would like to use CNN for time-series prediction problem. I have hourly solar irradiance data for 365 days. What I would like to do is training my network with 1 week data and predict next day.
<...
- 68
0
votes
1
answer
81
views
Using an image of data instead of the data when modeling
If we have many sequence data and corresponding plots, is there any reason we should use the image rather than the original data for deep learning?
Personally, I don't see any advantage of using CNN ...
- 177
1
vote
0
answers
360
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time series classification of an event either happening or not happening using machine learning techniques
I have sensor data that I would like to use to classify whether an an event (giving birth) is about to occur within (2-4hrs) in an animal based on various metrics collected by the sensor(activity ...
- 11
22
votes
2
answers
24k
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Convolutional neural network for time series? [closed]
I would like to know if there exists a code to train a convolutional neural net to do time-series classification.
I have seen some recent papers (http://www.fer.unizg.hr/_download/repository/KDI-...
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