Questions tagged [inceptionresnetv2]
The inceptionresnetv2 tag has no usage guidance.
17 questions
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Input dimensions for the EfficientNetV2 family of models
I have a question regarding the EfficientNetV2 family of models. If my understanding is correct there are 6 models under this family - B0 to B1 & S are the comparatively smaller models while M &...
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How to utilize the multilabel calssification labels during the course of training
I have a data set that consists of images. I am trying to perform multi-label classification on this data set. But the training labels consist of too many labels which are CSV file format. Now I find ...
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Deep Learning Classification Model for data with time dimension
I know it might be a generic question but I would still appreciate some feedback. So I have a dataset with 4 dimensions (time, x, y, color). Where I have a total of 24000 records each with (5, 188, ...
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CNN: visualize a model using its description
i created a Resnet model, which i want to show in a presentation, but i don't know how to visualize what i have done?
Is there a tool or something to get a graphic from the description of my model.
...
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What should be the input shape for convLSTM if ResNet-50 is applied before?
I have a video dataset, extracted all its frames, and applied ResNet-50 to extract features from all frames. ResNet-50 provides feature map of (2534, 7, 7, 2048), 2534 are the number of frames.
Now I ...
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Why trainable parameters are not considered right?
I have tested the "ResNet" block and it works fine, but when I call it in the model class, it somehow it does not work properly? Is it related to the model definition?
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Using vgg16 or inception with wights equals to None
When using pre-trained models like vgg16 or inception,
it seems that one of the benfits of using pre-trained model, is to save ...
- 527
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What does the phrase 'underlying mapping' mean?
In a paper by KaimingHe entitled Deep Residual Learning for Image Recognition, there is a phrase 'underlying layer'. What does this mean?
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Transfer Learning on Resnets/VGGs -- Validation accuracy can never be over 75%
I am trying to classify skin cancer images into two categories -- malignant and benign. Literatures suggest that using pre-trained resnet/vgg network achieves more than 90% accuracy. However, with my ...
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Error after merging two Deep Learning models VGG16 and ResNet50
I have merged two different models namely VGG16 and ResNet50 and given the outputs of the two models as input to another model. I have checked the Layers graph is correct. Before merging the code was ...
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Is it possible the model be better on a few epochs rather than hundreds of epochs?
I have very interesting experience in my CNN binary image classification. Do you think the result is by chance or there is a logic behind it?
I used InceptionV3 transfer with softmax (I know you will ...
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ResNet50 Overfitting even after Dropout
I have a dataset with 60k images in three categories i.e nude, sexy, and safe (each having 30k Images). I am using ResNet50 and observed that the training accuracy and validation accuracy is ok (...
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I'm trying to build a ResNet 18 model for Cifar 10 dataset, but I'm not able to fit the data dimension
At avergae pooling after the ConvNet, the error is displayed as the dimensions cannot be negative because the shape the previous output layer is 1,1,512 and on this the maxpooling cannot be done. Is ...
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Xavier initialisation vs He initialisation
After reading the famous paper, Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification, I understand two things:-
He initilization borrows on the benefits of ...
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Choosing a set of CNNs for paper
There are so many CNNs out there and I am trying to do a comparison between some of them in my paper. Which networks should I include? Resnet, VGG, and Inception are obvious, but I would like three or ...
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Keras Model question for Pre trained model extension
I want to add a few more layers to a Resnet50 model and my question is - do I need to compile it and train it on new data or can I just use it as it is? Will it just give me the Resnet50 results?
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CNN, sudden drop of accuracy between epochs, steps for improvements?
I am working on a text recognition problem, in which essentially I am trying to read images similar to captchas.
I implemented a ResNet in keras and I run it on colab with gpu.
Because I cannot ...
