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Questions tagged [convnet]

For questions regarding "Convolutional Neural Networks" (CNN)

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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 ...
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67 views

How to train two neural networks together

This could be considered as an extension of my previous question "How to make a region of interest proposal from convolutional feature maps?". Network 1: I have a multi-input neural network, it ...
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2answers
994 views

Can pooling ever increase accuracy in convolutional neural networks?

In ConvNets, pooling is used to downsize the input volume, leading to fewer parameters, leading to computational efficiency and possibly helping with overfitting. But can pooling ever increase the ...
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1answer
346 views

How to make a region of interest proposal from convolutional feature maps?

Problem Keras does not have any direct implementation of region of interest pooling. I am aware of how to perform maxpooling, but I don't know how to get bounding boxes from feature maps passed from ...
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18 views

Creating an image data set from a set of 2D points?

I have N sets of x and their corresponding y coordinates. e.g. x_i = [1.1, 2.3, 3.5] & y_i = [-1.1, -3.2, -5.2]. These coordinates represent an image, which may belong to one of two classes. I ...
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1answer
55 views

What is exactly meant by neural network that can take different types of input?

There is a scientific document that implements a convolutional neural network to classify 3 different types of data, although how exactly, is unknown to me. Here's the explanation of network ...
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0answers
62 views

Make image label prediction from Chainer CNN model

I have train dataset of 8000 images and labels. Validation set consists of 1957 images and labels. The test set contains 2487 images. Each image contains White Blood Cell images. WBC is divided innto ...
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1answer
22 views

Generated training set on convnet

I have a dataset with roughly 800 images that are classified in 18 classes. The classes are spread unevenly, with some classes having 30 images and others having 5. In order to increase my dataset,...
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1answer
69 views

Does it make sense to train a convolutional neural network on lo-res, use on hi-res pictures?

this is my first machine learning project and actually also my first question here. I am a novice to machine learning with a background in theoretical physics. I want to use a CNN to detect scratches ...
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1answer
836 views

What features are extracted from pre-trained model of CNN Keras?

I would like to use the CNN pre-trained model in feature extraction but I don't know what features are extracted from that. Please let me know!
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115 views

Dataset for GANs (logo generation)

I'm begining work on a new project that involves GANs. So far what I've learnt from some publications (e.g. this) is that these models require literally tonnes of images, e.g. 80K. The problem I'm ...
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1answer
107 views

Are there real world applications where deep fully connected networks are better suited than ConvNets

I would like to give some brief background for my question to avoid answers that explain the difference between fully connected nets and ConvNets. I completed the first 3 courses in the deep learning ...
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1answer
284 views

Difference between 1x1 Convolution and TimeDistributed(Dense())

Are these lines of code equivalent in Keras? From a few runs, they seem to be, and also intuitively since the channels dimension of my data is 1, my understanding is that a fully connected acts like a ...
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1answer
42 views

Performance of CNN based deep models with number of classes

How does a given deep cnn model performance vary with number of classes in tasks such as classification, object detection segmentation? For example mobilenet v2 gives around 90% accuracy on ...
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1answer
45 views

Wrangling data for CNN

I am using convolutional nets for a physics application. I am trying to figure out how to structure my raw data as an image for input into the CNN. I have $N$ samples. Each sample consists of the ...
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0answers
47 views

Training value neural network AlphaGo style

I have been trying to replicate the results obtained by AlphaGo following their supervise learning protocol. The papers specify that they use a network that has two heads: a value head that predicts ...
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1answer
549 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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4answers
99 views

What type of neural network should I use to detect meteors in images?

I am currently building a project that takes fisheye images from cameras and detects whether the picture contains a meteor, and if it does it tries to identify where the meteor is. The images look ...
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1answer
35 views

How would you a apply a cnn to do age estimation on static images? [closed]

After doing some reading on age estimation using the IMDB wiki dataset I wanted to try it out myself on a smaller scale but I dont quite understand the application of the CNN. Any clarification would ...
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1answer
389 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 ...
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1answer
143 views

How can I create a pixel labelled image for Semantic Segmentation?

I am following the Semantic Segmentation Examples tutorial by MathWorks. I understand that I can load pixel labeled images ...
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1answer
679 views

CNN backpropagation between layers

I have this CNN architecture: I know how to calculate error for weights based on the output and update weights between output<-->hidden and hidden<-->input layers. The problem is that I have ...
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2answers
231 views

Subsequent convolution layers

Note: I've read How do subsequent convolution layers work? a few times, but it's still difficult to understand because of the parameters $k_1$, $k_2$, and many proposals (1, 2.1, 2.2) in the question. ...
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0answers
156 views

How to train a multi inputs deep learning model using every combination of inputs? [closed]

I am beginner in deep learning. I want to create a multi inputs CNN model in Keras. The model takes two inputs of images to give the two images class. The two images from differnt datasets that have ...
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1answer
57 views

Print the prediction of convolutional neural network

I have designed a convolutional neural network using tensorflow which looks as follows ...
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1answer
336 views

CNN - Is this a Toeplitz Matrix?

I have been reading through Chapter 9 of www.deeplearningbbook.org, where convolutional networks are being described. The following image represents the output of a 2D convolution, without kernel ...
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0answers
17 views

Why is this convolution equation easier to apply than it's commutative counterpart?

The convolution is an operation on two functions of a real- valued argument. The convolution operation is typically denoted with an asterisk: s(t) = (x ∗ w)(t) ...
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0answers
78 views

Convolutional neural network for gray images

I am using vgg16 to design a CNN that takes gray input images. The model give me good results without changing anything related to colors. I am not sure if what I did is correct or not. I want to ...
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0answers
26 views

Deep Learning ROC and Average Precision Curve Results

I used Vgg16 to create a deep learning model and the dataset is imbalanced so, I used class_weight argument in fit_generator method. The model result as the following: accuracy= 98.9% and loss= 0....
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2answers
219 views

Does CNN take care of zoom in images?

Suppose a convolution neural network is trained on small images of an object, say flower, as in following 3 training images: Will this CNN correctly classify if the same object is present in zoomed ...
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1answer
1k views

Keras ImageDataGenerator.flow_from_directory doesn't find images

I'm working on a deep learning (CNN) problem. I have structured my images into folders correctly (I think), like this: ...
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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 ...
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1answer
4k views

How to make two parallel convolutional neural networks in Keras?

I created two convolutional neural networks (CNN), and I want to make these networks work in parallel. Each network takes different type of images and they join in the last fully connected layer. ...
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1answer
370 views

Check Overfitting in CNN

I am kind of new to NLP and text classification with Convolutional Neural Nets, and I have trained my first models quite recently. I am a little bit concerned with overfitting. I am doing multilabel ...
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1answer
21 views

Relation between amount of training samples and model depth?

When I add more hidden layers to my CNN (e.g. Dense Layers) it seems that the model needs more training samples to produce good results for classes with few training samples. In the single layer case ...
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0answers
35 views

CNN kernel location for input image

Given a CNN, say AlexNet: How could one relate kernel locations at the 3rd conv block, i.e 13x13 filter size to the input image. Would that give a meaningful representation in terms of the input ...
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1answer
37 views

How does training a ConvNet with huge number of parameters on a smaller number of images work?

I have two questions: I am wondering why is that a very deep model such as VGG-16 which has approximately 138 million parameters (Source) can be used as a model to be trained on just 1.3 million ...
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1answer
1k views

Shaping data for ConvLSTM for many-to-one image model

Ultimately, I am trying to obtain a binary segmentation mask for an image sequence. I have n number of image sequences, each with 500 greyscale images of size 256px by 400px. Each of these sequences ...
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: ...
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1answer
65 views

Too little or too much maxpooling?

I am creating a CNN in Keras where model.summary() shows: ...
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2answers
777 views

Overfitting in Siamese Network

I am trying to train a Siamese network for an application very similar to this and this. From what I have read about training Siamese networks dissimilar pairs of images outnumber the similar pairs ...
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3answers
1k views

Unbalanced training data for different classes

What precautions do I need to take while trying to develop a CNN for classification of images if there is much more training data for one label. For example: ...
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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 ...
5
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1answer
522 views

1x1 Convolution. How does the math work?

So I stumbled upon Andrew Ng's course on $1x1$ convolutions. There, he explains that you can use a $1x1x192$ convolution to shrink it. But when I do: ...
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0answers
766 views

Cross validation for convolutional neural network

I am using Keras to create a CNN model, and I would to use K-fold cross-validation to train the dataset. The dataset contains images and I am using ...
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0answers
66 views

how to load label data presented in raster format into Keras/Tensorflow

I want to use CNN network to segment 2 objects (binary: "0: object not present 1: object present") into shapes but I have an issue with data. The train data is 150 images and in "jpg" format and the ...
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1answer
293 views

How many Layers in the original Yoon Kim CNN implementation?

I saw some implementations of Yoon Kim's Convolutional Neural Network (Paper: http://www.aclweb.org/anthology/D14-1181).... ...in some implementations they put one more Dense(..) Layer before the ...
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2answers
935 views

What is the difference between using numpy array images and using images files in deep learning?

What is the difference between using numpy array images and using images files in deep learning? Which way is better?
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0answers
28 views

How to implement facial attendance system using less number of images of particulars

I have a project to implement facial Attendance where I have 5-6 images of particular and when individual comes, model should map the current image with person's earlier available images so if ...
2
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1answer
366 views

Should I use rescale parameters for data augmentation? [closed]

I am using Keras library to build a CNN model. I want to use data augmentation for training data. Should I use rescale parameters for data augmentation? ...