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Results tagged with cnn
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user 67200
Convolutional Neural Networks (CNN, also called ConvNets) are a tool used for classification tasks and image recognition. The name giving first step is the extraction of features from the input data.
3
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1
answer
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Accuracy decrease in production after adding additional input datas
I am trying to predict TimeSeriesA by using a CNN. I create snapshot images of the timeseries and these are then labelled.
With a very simple snapshot I get reasonable training and test accuracy. … Can a CNN be confused (wrong word!) by the additional data? …
- 75
1
vote
2
answers
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Why does my model sometimes not learn well from same data?
I have a dataset of 2 classes, both containing 2K images. I have split that into 1500 images for training and 500 images for validation.
This is a simple structure for testing purposes, and each imag …
- 75
1
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0
answers
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Why does SimpleNet achieve accuracy 0.9+ but AlexNet does not?
I am trying to classify some 224x224 RGB images.
I have 3 potential labels, but am currently only supplying training images for 2. My training set has approx. 2K images for both labels.
When I train …
- 75
0
votes
1
answer
282
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What could cause training CNN accuracy to drop after 7th epoch?
I am training a CNN on some new dataset.
Usually, the accuracy steadily improves over 10-20 epochs. …
- 75
1
vote
2
answers
133
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Why does adding random pixels stop my model learning in cnn?
I am using a very simple model to classify a 224x224 RGB image.
For a test, I have labelled my images (2 labels "Green" or "Red", 2,000 images of each) based on colour of a single fixed pixel from up …
- 75