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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My VGG16 Model's training and validation accuracy scores are stuck
Im trying to create an image classification model that classifies plants from an image dataset made up of 33 classes, the total amount of images is 41,808, the images are unbalanced but that is ...
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2
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Tensorflow: How to pass multiple images to VGG16 layers
This is a toy problem I am working on. I have an extruded N-sided polygon that I have rendered from 5 different randomly selected viewpoints. The classification task is to determine the number of ...
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Clustering methods for text and image features
I want to build a recommender system with unlabeled data and used TF-IDF to extract text features from a given short description and VGG-16 to extract image features. I am looking for a way to combine ...
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Combining text and image features with different scales
I have computed text features using [SBERT][1] and image features using VGG-16. The text features range from -1.58 to 1.58, whereas the image features range between 0 and 521. I would want to ...
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Getting bad accuracy of classification using Keras VGG-16
I am very new to the data science domain and directly jumped to TensorFlow models. I've worked on examples provided on the website before. My first time doing any project using it.
I am building an ...
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Random Forest Classifier is giving me an array of zeroes
I used VGG16 as feature extractor on a dataset with 9 classes and trained the Random Forest Classifier on the feature vector. I tried to make prediction on the test feature vector but the prediction ...
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Multiple Images as input for Tensorflow VGG16, and how can it be realized
So I am trying to vgg16 as a feature extractor for my set of Partial Angle CT reconstructions(so each set of reconstructions contains 22 individual grayscale images(128,128) that I reshaped into a (...
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Not able to understand Transfer Learning with Vgg16
So, I have to work with Vgg16 in my semester group project, and was following this to do transfer learning.
I don't understand CNN much, but am learning currently.
The very first problem was that ...
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Why VGG16 Outperforms VGG19?
I built VGG16 and VGG19 models using transfer learning. As far as I know, VGG19 has more convolutional layers and it is more complex, VGG16 performs better in terms of accuracy and loss. I can't ...
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Invalid argument error: logits and labels must be broadcastable
Whenever I try to execute this vgg16 code I get an error like this:
...
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How to increase FER2013 dataset validation_accuracy for only 3 classes i.e, happy,sad,neutral?
I am building a face emotion detection model using vgg16.
Using FER2013 dataset
for 7 classes i am getting=
train_accuracy=97%, validation_accuracy=90%.
but when i tried with 3 classes i.e, happy,sad,...
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Hello guys, is dimension reduction required for tensorflow? [closed]
I am working on face emotion detection using FER2013 dataset using tensorflow and vgg16 model.
I am applying t-sne to my training dataset for dimensionality reduction.
My question is that "is ...
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Finding the optimum sample lenght for sound recoginition
I am working on a sound recognition problem with a self-made data set of very long recordings. My current process looks like this:
Time series segmentation to extract sound events cropped to a fixed ...
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Low accuracy VGG16 model when using ImageDataGenerator.flow_from_directory but high accuracy using image_dataset_from_directory as inputs
I am currently trying to understand why is it that a certain model gives very different accuracy results when using two different ways to input the same training dataset to train it.
I have the ...
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extract features from low resolution
I have medical images and need to extract features from the layer before the classification layer using VGG for example but the ...
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1
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What is the difference between features in vgg
I read the architecture of the model but this is the first time I try to use it . The calculations of the features map will be different if I extract the features from the two last layers or from the ...
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I am looking for general image-based clustering methods
My task is to cluster some images, I decided to use the VGG model to extract the features and then use K-Means to cluster these features.
But my question: When I use a VGG as a feature extractor, I ...
user119783
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Shared classifier for 3 neural networks (is this weights sharing?)
I would like to create 3 different VGGs with a shared classifier. Basically, each of these architectures has only the convolutions, and then I combine all the nets, with a classifier.
For a better ...
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How to get >=85% accuracy on 3-class classification task
Now I am solving the problem of 3-class classification (in the task you need to understand who is in the picture - a panda, a cat or a dog). The dataset consists of 3000 images. To solve the problem, ...
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1
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What should the output sizing be for a class that returns multiple image arrays for a dataloader
I have a custom image class (mainly borrowed from examples) that takes in an image of size 3x244x244 for use in a VGG model and returns augmented versions (rotations of 90,180,270 and an Hflip). ...
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Is there wights of voice or audio for VGG or Inception?
I want to use VGG16 (or VGG19) for voice clustering task.
I read some articles which suggest to use ...
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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 ...
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Plot a training/validation curve in Pytorch Training [closed]
I have the following training method and I'm confused how may I modify the code to plot a training and validation curve history graph with matplotlib
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How Does EAST detector implementation with VGG16 look? How many outputs does it have?
I was reading the Efficient and Accurate Scene Text Detector paper and saw the author reference VGG-16 as a possible stem "feature extractor" network. In the paper they say:
In our ...
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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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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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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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2
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596
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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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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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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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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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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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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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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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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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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:
...
user84391
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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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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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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:
...
user84391
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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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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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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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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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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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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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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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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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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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