All Questions
11 questions
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19
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My CNN validation Accuracy increases super slow?
im doing a retinopathy detection project with over 3500 images, 700 in each class. I've filtered the image like
It seems that my model isn't learning from the data, or is having trouble because the ...
- 1
1
vote
1
answer
639
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Which epoch is the best for me to choose?
I have trained my deep learning model. I also saved the validation loss to a file and plotted on a graph
I have $2$ questions for this:
Does the validation loss look normal? Is there any issue with ...
user78437
1
vote
1
answer
89
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Why training the same model on the same data can be slower on better card?
Can someone explain why training CNN model (in my case DenseNet201) on the same data, and the same data processing pipeline can be slower on better GPU (RTX3090) than worse one (RTX3060), with the ...
- 1,280
0
votes
0
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95
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Feeding the output back to input in 3D CNN model
I am currently designing a Model which takes Input 3D Grid and Model Output at $t-1$. The model figure is described below
I have two thoughts in training the model for above situation.
Feed output $...
- 1
1
vote
2
answers
757
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How to handle images that don’t pertain to image classifier at all?
I am trying to create a CNN model that classifies if a person is wearing a seatbelt or not to verify they drive safely. I know to get images of people wearing seatbelts and people not wearing ...
2
votes
1
answer
147
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How many layers exists in my neural network?
I have a neural network model defined as below. How many layers exist there? Not sure which ones to count when we are asked about the number.
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- 983
1
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0
answers
26
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Training dataset for convolutional neural network classification - will images captured on the ground be useful for training aerial imagery?
I am an agronomy graduate student looking to classify crops from weeds using convolutional neural networks (CNNs).
The basic idea that I am wanting to get into involves separating crops from weeds ...
- 129
1
vote
1
answer
41
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Semantic issues with predictions made by my trained model
I'm new to Deep Learning. I used Keras and trained a inception_resnet_v2 model for my binary classification application (fire ...
- 983
2
votes
0
answers
20
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Binary annotations on large, heterogenous images
I'm working on a deep learning project and have encountered a problem. The images that I'm using are very large and extremely detailed. They also contain a huge amount of necessary visual information, ...
- 21
13
votes
2
answers
7k
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Which layer in a CNN consumes more training time: convolution layers or fully connected layers?
In a convolutional neural network, which layer consumes more training time: convolution layers or fully connected layers?
We can take AlexNet architecture to understand this. I want to see the time ...
- 325
2
votes
1
answer
2k
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What fast loss convergence indicates on a CNN?
I'm training two CNNs (AlexNet e GoogLeNet) in two differents DL libraries (Caffe e Tensorflow). The networks was implemented by dev teams of each libraries (here and here)
I reduced the original ...
- 131