Questions tagged [vgg16]
The vgg16 tag has no usage guidance.
34
questions
0
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1answer
20 views
Semantic segmentation with greyscale images
I'm trying to reproduce a research with greyscale images instead of colour images.
I have found that there are pre-trained networks, like VGG16, with ImageNet. But that dataset has colour images, and ...
0
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0answers
15 views
Transfer learning by using vgg in pytorch
I am using vgg16 for image classification. I want to test my transfered model with the following code:
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0answers
11 views
Do we train a feature extractor or we just use a trained network as a feature extractor?
I've just started to learn Tensorflow and Keras.
I'm using Tensorflow 2.1.0 and Keras 2.3.7.
I'm using this network as a feature extractor. Well, I'm trying to use it:
...
1
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0answers
25 views
class activation mapping when accuracy is 100%
I am a beginner to image classification and apologies beforehand if the question I am asking is dumb. I am currently using the following model:
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0answers
19 views
Why the validation accuracy does not increase in a normal way over the epochs?
I'm trying to transfer learning VGG16 model with imagenet in a dataset of retinal images but i'm confused to get a graph like this in the picture below, I don't know why the validation accuracy didn't ...
2
votes
1answer
131 views
How to combine different models in Keras?
I have a pre-trained network, consist of two parts, the feature extraction, and the similarity learning.
The network takes two inputs and predicts the images are same or not.
The feature extraction ...
1
vote
2answers
77 views
Why is VGG16 training accuracy is constant?
I want to train a model using VGG16 to classify radio signals by their modulation typ. similar to this paper (Over the Air Deep LearningBased Radio Signal Classification) So I have built the model ...
2
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0answers
95 views
Why is convnet transfer learning taking so long?
I am using transfer learning to train a binary image classification model using keras' pretrained VGG16 model. The code can be found below :
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0answers
10 views
GIven some similar pictures,how to detect and mark the differences among these picture by deep learning
Now i have certain images ,they can be classfied into tow groups :right and false .However, two sorts just have small differnece in the detail . (for example ,I possess two maps. Their content is ...
1
vote
1answer
155 views
Why/When should I use VGG16 to do fine-tuning? [closed]
Why or When should I use VGG16 in my cnn? what is the pros and cons to use this model?
I search but not found this answer. If you have references, I appreciate
0
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2answers
171 views
CNN implementation low accuracy on MINST data
I'm trying to implement VGG11 (Model A of Table 1 from this article) on the MINST dataset but I'm getting ~10% train & test accuracy (as bad as random guessing). I had to resize the MINST data ...
0
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0answers
66 views
VGG style transfer fails with pre-computed `vgg19.preprocessing()` for the content, transfer, style inputs
I'm working through the style transfer tutorial on tensorflow, see: style transfer
I made a few adjustments to my notebook, but it works fine for the base case:
[ content_image | transfer_image | ...
1
vote
1answer
193 views
How can I increase my accuracy avoiding overfitting? CNN-Keras-VGG16
As I asked in this question: Why are my predictions bad, if my accuracy in train is roughly 100% (Keras CNN) , my problem was Overfitting, so, I reduce the number of layers, and now I have this model:
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1
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1answer
585 views
How to fine tuning VGG16 with my own layers
I want to maintain the first 4 layers of vgg 16 and add the last layer. I have this example:
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2
votes
1answer
13 views
How to find which patch in orignal image does an activation correspond to in vgg net after the final pooling layer
So I am working on the NeurIPS 2019 reproducibility challenge, The link to the paper is https://arxiv.org/abs/1806.10574. So basically we have a vgg-16 net with the final fully-connected layers ...
4
votes
2answers
149 views
Why are my predictions bad, if my accuracy in train is roughly 100% (Keras CNN)
In my CNN i have to handle 2 classes in a binary system, I have 700 images each class to train, and others to validation. This is my train.py:
...
0
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0answers
15 views
Removing layers from a convolutional encoding-decoding network
I've been reading this paper on Style-transfer (Universal Style Transfer via Feature Transforms):
A crucial part of the algorithm (Section 3.3) uses a pre-trained VGG-19 network as an encoder to ...
0
votes
1answer
72 views
Can I save only some VGG19's layers into a .H5 file?
I am training a deep-learning style transfer model with the pretrained-VGG19 CNN.
My aim is to use it in my Android app for personal purposes with Google Firebase Machine Learning Kit (which would ...
1
vote
1answer
314 views
How to increase the accuracy of my predictions (CNN fine tuning VGG16 KERAS)
In my VGG16 fine-tuning, I have to classify retinal images in 2 classes (or 4th stage or not 4th stage) and I have 700 images each class to train. This is my code now:
...
5
votes
2answers
178 views
vgg16 needs less epochs than resnet ,why?
Recently i Have been comparing the vgg16 with resnetv1 with 20 layers.I have found out that although each epoch on vgg takes more time to complete,it generally needs less epoch to reach a certain ...
0
votes
1answer
465 views
Transfer learning VGGish (AudioSet). Impact of zero padding to fit the input size
I am trying to train a network on top of the VGGish architecture (https://github.com/tensorflow/models/tree/master/research/audioset/vggish), using (transfer learning) finetuning.
I initially started ...
0
votes
1answer
80 views
How to find the class name of a new image from the pre-trained model
I would just like to get the class names of the predictions. I can get the class names on the images that I trained the model. But if I predict an image (say which is not trained but already belongs ...
5
votes
2answers
3k views
Is Faster RCNN the same thing as VGG-16, RESNET-50, etc… or not?
My understanding is that Faster RCNN is an architecture for performing object detection. It finds objects in an image and classifies them. My understanding is also that VGG-16, RESNET-50, etc... also ...
0
votes
1answer
9 views
Key pixels, key “features” detection in CNNs
I am working on a dataset but I don't know what the labels mean.
I was wondering if using CNNs there was a way to understand which pixels where most significant for the network.
A little bit in the ...
0
votes
0answers
801 views
Improve accuracy of Keras multiclass image classification with pretrained VGG16 conv_base
In the moment, I'm training my first "larger" image classification model with Keras (22 classes, 2000 train samples, 500 val samples each class). I use a pretrained model (VGG16). My current model is ...
3
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3answers
1k views
Neural Network Model using Transfer Learning not learning
I am a beginner in Deep Learning and working on Road Crack detection using transfer learning. I am working on binary classification with two classes , crack and no crack.
My distribution of two ...
2
votes
0answers
80 views
How to apply only 3 layers of a network to a data
I want to use the 3rd layer's output of the VGG16 network. The error is like below:
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2
votes
1answer
63 views
How to calculate $\phi_{i,j}$ in VGG19 network?
In the paper Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network by Christian Ledig et al., the distance between images (used in the loss function) is calculated from ...
1
vote
1answer
2k views
How to save prediction values for the whole data in Keras
I am using pre-trained VGG16 model to classify images located in the folder. Currently, I am able to classify only one single image.
How can I modify the code to classify all the images in the ...
0
votes
1answer
80 views
Image features (produced by VGG19) do not properly train an ANN in Keras
I've used a VGG16 network to extract features from an image dataset, creating a features dataset using the following code:
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3
votes
1answer
1k views
Overfitting in CNN
I am training a VGG net on STL-10 dataset
I am getting Top-5 validation accuracy about 98% and Top-1 validation accuracy about 83%
But both the Top-1 and Top-5 Training accuracy is reaching 100%
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3
votes
2answers
567 views
Is this an over-fitting case?
I'm a new programmer and this is my first ever neural network for real world application.
Here is the deal, I'm using a top-less pre-trained VGG-16 with some dense layers on top of it.(for image ...
5
votes
2answers
9k views
Why is input preprocessing in VGG16 in Keras not 1/255.0
I am just trying to use pre-trained vgg16 to make prediction in Keras like this.
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1
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2answers
2k views
