Questions tagged [convnet]

For questions regarding "Convolutional Neural Networks" (CNN)

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2
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2answers
190 views

How to determine the number of the training images in Keras after data augmentaion?

I want to create a CNN model and I am using data augmentation. I want know the number of augmented images in Keras. How to determine the number of the training images in Keras after data augmentation?...
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1answer
546 views

Question about “1x3 and 3x1 conv is equivalent to 3x3 conv”

I see a lot of sites talk that we can substitute 1x3 conv + 3x1 conv for 3x3 conv. In order to demonstrate easily, we use a 3x3 image as an example. From the point of view of parameters, I know that ...
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1answer
102 views

Doing a fine tuning after a transfer learning

I red about fine tuning and transfer learning for CNNs and I was wondering if we can do fine tuning after using transfer learning on the same CNN , if so will this increase the performance of the ...
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1answer
11k views

back propagation in CNN

I have the following CNN: I start with an input image of size 5x5 Then I apply convolution using 2x2 kernel and stride = 1, that produces feature map of size 4x4. Then I apply 2x2 max-pooling with ...
3
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1answer
37 views

What do positive and negative gradient values mean for Convolutional Neural Network?

As we have the typicall pass of the neural network we make a forawrd pass to predict classes and then we have cost function and based on that we calculate gradients. I'm wondering what are the ...
2
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1answer
37 views

Model not learning when using transfer learning

I am working on a personal project on image classification (two classes) and am trying to see how the MobileNet v2 structure would perform. While training the training accuracy is already quite high ...
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1answer
24 views

Magnification factor in image classification

If a CNN is trained on images focusing on an object, will it also recognize when multiple such objects are present in the image? For example can a network trained on single flower images also ...
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0answers
17 views

Understanding the significance of LeNet-5 w/ MNIST data set

I'm beginning to learn about conv nets and started with what I understand to be one of the seminal works: LeNet-5. However, my limited experimentation doesn't seem to show any advantage over a single ...
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2answers
22 views

ConvNet with concatenated data

I have a basic question regarding convolutional neural network. Assume I have a set of 1000 RGB images and I train a CNN from this set. I can obviously split each of my RGB images into 3 different ...
0
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1answer
28 views

Tensorflow Conv3D with variable input size

I have a hypotethical question: Is it possible to train Conv3D with variable input size? Sample dim = Length x Width x Depth ; Depth are fixed per each samples, let's say 500. However Length x Width ...
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2answers
3k views

How to properly save and load an intermediate model in Keras?

I'm working with a model that involves 3 stages of 'nesting' of models in Keras. Conceptually the first is a transfer learning CNN model, for example MobileNetV2. (Model 1) This is then wrapped by a ...
3
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1answer
40 views

Is there any work done on reconfigurable convolutional neural networks?

Convolutional Neural networks are used in supervised learning meaning models are always "set in stone" after training (architecture and paramters) so this might not even be possible, but is there any ...
0
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1answer
27 views

How neural style transfer work in pytorch?

I am using this pytorch script to learn and understand neural style transfer. I understood most part of the code but having some hard time understanding some parts of the code. In ...
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3answers
279 views

How to combine GridSearchCV with Early Stopping?

I'm a beginner in machine learning and want to train a CNN (for image recognition) with optimized hyperparameter like dropout rate, learning rate and number of epochs. The optimal hyperparameter I ...
0
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1answer
384 views

How to increase accuracy of model from tensorflow model zoo?

Situation: My dataset is 70k images of people wearing clothes. Images are labeled: bbox position and class. There are 10 classes. I did 80:20 split. Categories are balanced with exception of one ...
0
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1answer
190 views

Setting input shape for an NLP task in R(Rstudio) using keras 1D convolution layer, when it expects 3 dimensional input (a tensor)

I am using R programming language and using Keras API to build a functional 1D CNN. I have a matrix of my dataset of the following shape rows*features (6000*1024). The input layer is set using the ...
7
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1answer
995 views

What is the memory cost of a CNN?

I was recently thinking about the memory cost of (a) training a CNN and (b) inference with a CNN. Please note, that I am not talking about the storage (which is simply the number of parameters). How ...
2
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0answers
19 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 : ...
2
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1answer
25 views

How do CNNs find different feature maps?

Assume I have a CNN that in the first (conv) layer takes a 1-channel signal (the input) and gives a 2-channel output. Let's further assume that the rest of the net has symmetric architecture from the ...
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0answers
9 views

Train a competitive layer on nonnormalized vectors using LVQ technique

How can we train a competitive layer on non-normalized vectors using LVQ technique ? The net input expression for LVQ networks calculates the distance between the input and each weight vector ...
2
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1answer
137 views

Tensorboard with pytorch dont display a graph

I am trying to visualize a model I created using Tensorboard with Pytorch but when running tensorboard and going to the graph tab nothing is shown, im adding my code for reference, also im adding a ...
3
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1answer
545 views

Keras bug NasNetlarge no top

I am trying to use NasNetlarge in Keras without the top but I cant get rid of the top: ...
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2answers
25 views

How to extract crucial features to create an image

Imagine, you have a dataset containing pictures of (example only, just to explain the task) cats and dogs. The data set is labeled, so we can train using supervised learning algorithms. My goal is to ...
1
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1answer
40 views

Which combination of 3 hyperparameters to combat overfitting of a convolutional neural network?

I have a small dataset with which I want to train a CNN by using Data Augmentation. Since the CNN is overfitting due to the small data set, I would like to optimize some hyperparameters. However, ...
0
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0answers
10 views

Modifying network to handle images consistently

I'm modifying IRNet to work with the Cityscapes dataset. This network takes images as input and is supposed to output images that can be used as instance segmentation labels. IRNet originally uses ...
3
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1answer
112 views

Why is training and validation loss steadily rising (eventually to NaN) in this CNN of mine?

Dear ML and data scientists: I have 4 layers of gray scale images for every single biological specimen in my dataset. I am trying to train a 4-convolution CNN (see pytorch architecture below) to ...
4
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1answer
1k views

Gradient flow through concatenation operation

I need help in understanding the gradient flow through a concatenation operation. I'm implementing a network (mostly a CNN) which has a concatenation operation (in pytorch). The network is defined ...
1
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1answer
16 views

Validity of PU learning while using character-level encoding using CNNs for classifying text data

I'm trying to classify a large set of documents (~100M) as valid or invalid, based upon a small given set of labeled valid documents (~3k). I'd like to know if the PU learning approach described in ...
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1answer
34 views

Improve performances of a convolutional neural network

I am doing image classificaition, and to do this I have built the following neural network: ...
4
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1answer
8k views

Keras Conv1D for simple data target prediction

I am trying to use conv1D layer from Keras for predicting Species in iris dataset (which has 4 numeric features and one categorical target). Following is my code: ...
2
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1answer
155 views

MLP conv layers

When should MLP conv layers be used instead of normal conv layers? Is there a consensus? Or is it the norm to try both and see which one performs better? I would love to better understand the ...
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0answers
831 views

Neural Network: how to interpret this loss graph?

I have built a deep CNN with TensorFlow that does not classify on one-hot encoded vectors but probability distributions, i.e. given some input $X$ I feed a normal distribution $\mathcal{N}(\mu, \sigma^...
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0answers
5 views

if two convolution layer connected in tandem follow associative property of convolution?

Two Convolution filter follow the associative property as follows :- I want to ask whether this property will hold for two convolution layer with no operation in between them?
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2answers
161 views

Keras Conv1D model Input_shape value error

I am not sure why I am receiving this value error. Additionally, I haven't found a tutorial that explicitly talks about the appropriateness of size of filters and kernel. I would appreciate some input ...
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1answer
27 views

To calculate my confusion matrix with recall and precision, my test set need to be equal(balanced)?

In my CNN, I have 200 'negative' images and 50 'positive' images in my test set and I want to make a confusion matrix. My doubt is if I have to equalize the samples in the dataset because if I keep ...
0
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1answer
35 views

Reason for Training and test loss sudden increment after some epochs keras

We know that if training and test loss are different from each other, our model is over-fitting. However, if both get high after some epochs, how can we justify it? One way to solve it is to reduce ...
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0answers
109 views

Python Keras model performs much worse than R Keras model

I got this R Keras model from GitHub that performs really well. GitHub repo ...
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3answers
219 views

Model Validation accuracy stuck at 0.65671 Keras

I am using conv1d to classify EEG signals, but my val_accuracy stuck at 0.65671. No matter what changes i do, it never go beyond 0.65671. Here is the architecture ...
7
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4answers
15k views

how to calculate the output shape of conv2d_transpose?

Currently I code a GAN to generate MNIST numbers but the generator doesnt want to work. First I choose z with shape 100 per Batch, put into a layer to get into the shape (7,7, 256). Then ...
1
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1answer
49 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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0answers
32 views

Why when I apply GaussianBlur in my images, my model overfit? CNN KERAS

I have 1400 images (700 each class), and i'm using vgg-16 to classificate between one and other class. But when I apply the preprocess method Gaussian Blur (which seem to be very much clear to see the ...
1
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1answer
360 views

What is the best architecture for Auto-Encoder for image reconstruction?

I am trying to use Convultional Auto-Encoder for its latent space (embedding layer), specifically, I want to use the embedding for K-nearest neighbor search in the latent space (similar idea to ...
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0answers
39 views

Combining 2D Detection with Disparity Maps to Learn 3D Object Geometry

Since the disparity map above is a representation of the object's distance from the camera's origin, is it reasonable to assume that a network (perhaps a convolutional LSTM) could be trained to ...
5
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3answers
3k views

Faster-RCNN how anchor work with slider in RPN layer?

I am trying to understand the whole Faster-RCNN, From https://www.quora.com/How-does-the-region-proposal-network-RPN-in-Faster-R-CNN-work Then a sliding window is run spatially on these feature ...
1
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1answer
157 views

LeNet-5 - combining feature maps in C3 layer

Famous LeNet-5 architecture looks like this: The output of layer S2 has dimension: 10x10x6 - so basically an image with 6 convultions applied to it to derive features. If each dimension was again ...
2
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0answers
29 views

Did I do the right thing in my CNN Keras (class imbalance - augmentation)

To implement my Binary CNN in keras, I had a dataset of ~~35000 images but only 700 is from one class and all the others are from the other class, so what I did: I get the 700 unique images from class ...
0
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0answers
16 views

How do I augment data after spliting traininng datset into train and validation set for CIFAR10 using PyTorch?

When classifying the CIFAR10 in PyTorch, there are normally 50,000 training samples and 10,000 testing samples. However, if I need to create a validation set, I can do it by splitting the training set ...
0
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3answers
51 views

Problem with overfitting

I make small CNN from scratch to classify barcodes. I have two classes: one for images with barcodes and second for all what isn't barcodes (items, animals, landscape, furniture, people). I got good ...
0
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1answer
28 views

What is a latent space vector?

I do not understand this about GANs. Apparently the Generator is supposed to receive a latent space vector as its input. Yet I couldn't find an example of how I can implement it in Pytorch. This is a ...
0
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0answers
18 views

CNN model with transfer learning not performing, training loss is still high, test accuracy is very low

Hi I'm trying to train a cnn model with transfer learning, and I am not able to get a good test accuracy (14%) - I don't know why it doesn't work for me. ...