Questions tagged [vgg16]

Use for questions about VGG16, the Convolutional Neural Network (CNN) model developed by researchers at the University of Oxford.

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8 views

Validation Accuracy / Loss plateaus regardless of learning rate (VGG 16)

I am trying to classify my dataset into two categories using transfer learning with vgg and finetuning the very last layer (fully-connected). When I plot the graph of value vs epochs, I get the ...
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24 views

VGG16 based model not learning to recognize emotions from videos

My model looks like this ...
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1answer
81 views

What is Deep learning approach to count the number of Diamonds in an image?

I am working on a project which involves counting the number of diamonds in the provided image. I have a set of images and a VIA annotated .json file which has all the annotations. How do I proceed ...
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1answer
24 views

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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1answer
28 views

Training Accuracy is getting higher, but Valid Loss and Accuracy is same every epoch

I'm doing a transfer learning with ResNet50. My dataset is clothes(224x224x3), and 49 category(classes) -> training data 1000 per 1 category, total 49000. And valid data 200 per 1 category, total ...
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1answer
41 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 ...
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18 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: ...
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0answers
28 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
26 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 ...
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1answer
726 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 ...
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2answers
149 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 ...
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1answer
179 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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1answer
359 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
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2answers
250 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 ...
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1answer
346 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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1answer
1k 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: ...
2
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1answer
17 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 ...
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2answers
158 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: ...
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1answer
125 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 ...
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1answer
558 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: ...
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3answers
261 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 ...
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1answer
580 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 ...
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1answer
137 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 ...
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2answers
4k 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 ...
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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 ...
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0answers
970 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 ...
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3answers
2k 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 ...
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0answers
82 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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1answer
77 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 ...
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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 ...
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1answer
82 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: ...
3
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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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2answers
660 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 ...
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2answers
10k 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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2answers
2k views