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Questions tagged [convolutional-neural-networks]

For questions about convolutional neural networks, also known as CNN or ConvNet.

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1answer
13 views

How can max pooling be applied to find features in words?

I'm reading about max pooling in a dynamic CNN paper and I can see how it can help find features in images cause the pixel with the highest density gets pooled, but how does it help find features in ...
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1answer
20 views

Convolutional filters: create new ones

I'm studying a Master's Degree in Artificial Intelligence an my final work is about Convolutional Neuronal Networks. I was looking for information about filters (or kernel) at the convolutional ...
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17 views

How to count pixels in a object mask which is segmented using Mask R-CNN?

I have segmented concrete cracks from concrete structure images using Mask R-CNN. Now I need to measure the length of the segmented masked crack. Will the pixel counting method work? Can anyone help?...
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5 views

Loss function for increasing the quality of the image when labels are not perfectly alligned

I am trying to increse the quality of the images that I gather from the microscope. That is a acoustic microscope and there are lots of technical details but in a nutshell the low quality images and ...
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0answers
10 views

Size of image input of neural networks while resizing may not be appropriate

I have the following problem while using convolutional neural networks to detect forgeries: Resizing the image to fit the required input size may not be a good way because the forgery detection ...
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1answer
23 views

What could I do to this CNN to achieve a higher accuracy on the cifar10 dataset?

I have achieved around 85% accuracy using the following architecture: I used a learning rate of 0.001 and trained the model over 125 epochs with a batch size of 64. Any suggestions would be much ...
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1answer
26 views

Semantic issues with predictions made by my trained model

I'm new to Deep Learning. I used Keras and trained a inception_resnet_v2 model for my binary classification application (fire ...
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1answer
34 views

ValueError: Error when checking target: expected dense_3 to have shape (1,) but got array with shape (2,)

I am trying to build a CNN model on Keras. The data has a dimension of 921 rows × 10000 columns. Here is the code: ...
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7 views

Plot class activation heatmap of Caffe Model in Python

Given the following 3 research papers, the authors have shown different heatmap graphical representations for features of the trained CNN models: On the performance of Convnet feature for place ...
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4answers
74 views

What are examples of books or papers on the details of convolutional neural networks?

I'm studying a master's degree and my final work is going to be about the convolutional neural network. I read a lot of books and I did Convolutional Network Standford's course, but I need more. Are ...
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1answer
32 views

Making a CNN for phoneme classification

I was making a simple phoneme classification model for a 10 week-long class project and I ran into a small question. Is it possible, to create a model that takes a 1-second (the longest phoneme is 0.2 ...
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1answer
15 views

Best approach for 2D Grid Image Segmentation

I'm working on a project where I need to extract text from grocery discount flyers like the Costco announcement below (retrieved in a random google search, Costco is not the deal here): If I just run ...
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1answer
21 views

Interpreting Keras Yolov3 config file [on hold]

How does one interpret the "min_input_size", "max_input_size" and "anchors" fields in the Yolov3 config file here. In particular, suppose we have the following: ...
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1answer
38 views

Is it possible to train a CNN to predict the dimensions of primitive objects from point clouds?

Is it possible to train a convolutional neural network (CNN) to predict the dimensions of primitive objects such as (spheres, cylinders, cuboids, etc.) from point clouds? The input to the CNN will be ...
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1answer
42 views

What is the fastest way to train a CNN with billions of examples?

I have a CNN model that I need to train for a large scale genomics application. It is working well with a subset of my training data. I have scaled up to a subset of about 130 million examples and ...
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6 views

How to measure object size from the disparity map using CNN?

I am a student learning about image processing using CNN. I want to learn how to measure the object size from the disparity map obtained from left and right stereo images.
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11 views

How to measure the size of an crack which is segmented from an image using Mask-RCNN?

I am a masters student going to work in a project to analyze the cracks in underwater concrete structures. I need some suggestions for data acquisition and length measurement of the crack. I have ...
2
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1answer
36 views

Pose estimation using CNNs on Point clouds

In the case of single shot detection of point clouds, that is the point cloud of an object is taken only from one camera view without any registration. Can a Convolutional Network estimate the 6d pose ...
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0answers
13 views

How to properly use batch normalization during inference

I am trying to manually implement calculations of the image classification process using pre-trained weights from the MobilenetV2 network. I know how to apply filter weights to the channels, but not ...
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2answers
66 views

Wouldn't convolutional neural network models work better without flattening the input in any stages?

The above model is what really helped me understand the implementation of convolutional neural networks, so based on that, I've got a tricky hypothesis that I want to find more about, since actually ...
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0answers
18 views

Ideas on a network that can translate image differences into motor commands?

I'd like to design a network that gets two images (an image under construction, and an ideal image), and has to come up with an action vector for a simple motor command which would augment the image ...
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1answer
30 views

Is it better to adjust the natural lighting (while recording the video) or to subsequently apply filters on the original video?

For the purpose of object detection, is it better to adjust the natural lighting (while recording the video) or to apply filters (e.g. brightness filters, etc.) on the original video to make it ...
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7 views

How to set loss weight to zero for an output dimension in keras?

Suppose I am training a model to detect facial keypoints that allow occlusions to be present. The input is an image of a face, and the model has to predict the x,y coordinate of both eyes and mouth. ...
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19 views

How to implement CNN with variable number of images in tensorflow or keras?

Suppose I have a problem where I want to classify the color of LEDs seen in the image. I can use OpenCV to pinpoint the exact location of these LEDs but I do not know their color for sure because the ...
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1answer
48 views

Do models train better if the dataset is more specific? (Semantic Segmentation / Bounding Box / Image classification)

I'm working on a project where there is a limited dataset of videos (about 200). We want to train a model that can detect a single class in the videos. That class can be of multiple different types ...
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1answer
28 views

Is it possible to vectorise a CNN?

I am trying to write a CNN from scratch and am wondering if it possible to vectorise the convolution step. For example, if I had a dataset of 500 RGB images of size 32x32x3, and wanted the first conv ...
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1answer
15 views

Should I use my redundant feature as an auxiliary output or as another input feature?

For example, given a face image, and you want to predict the gender. You also have age information for each person, should you feed the age information as input or should you use it as auxiliary ...
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0answers
13 views

CNN multi output scores and evaluation

I am building a CNN with two outputs. I still have to put time in the network itself, but I was trying to get a good evaluation/classification report of the results. My code is the following: ...
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0answers
4 views

Would models like U-Net be able to segment objects which has label based on its surrounding context?

Suppose that we want to segment a red blob from the image, normally you will have a class for this red blob e.g. 0. And every red blob you detected will have a class of 0. But in my case, I want that ...
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1answer
6 views

Positioning of batch normalization layer when converting strided convolution to convolution + blurpool

I'm trying to replace the strided convolutions of Keras' MobileNet implementation with the ConvBlurPool operation as defined in the Making Convolutional Networks ...
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1answer
20 views

Is a VGG-based CNN model sometimes better for image classfication than a modern architecture?

I have an image classification task to solve, but based on quite simple/good terms: There are only two classes (either good or not good) The images always show the same kind of piece (either with or ...
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1answer
38 views

Are there well-established ways of mixing different inputs (e.g. image and numbers)?

I am interested in the possibility of having extra input along with the main data. For instance, a medical application that would rely mostly on an image: how could one also account for sex, age, etc.?...
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1answer
38 views

What are the features get from a feature extraction using a CNN?

I've just started to learn CNN and somewhere I have read if I remove the last FCL I will get the features extracted from the input image but... what are those features? Are they numbers? Labels? An ...
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1answer
25 views

How can I use feature extraction in CNN with image segmentation?

I'm just started to learn about meta learning and CNN and in most paper that I've read they mention to have one CNN to feature extraction. These features will help the another network. I don't know ...
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1answer
32 views

Calculating Weights for CNN Max Pooling Output

How do i calculate weights for max pooling output? For example if there are 10 inputs, a pooling filter of size and a stride 2, how many weights including bias are required for the max pooling output ...
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0answers
18 views

Which neural network algorithms can be used to map motion vectors in image processing?

I'm working on finding out the motion vectors of objects in images. The inputs are the images of objects in motion. The outputs of neural network are the object name, direction of object vector and ...
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2answers
56 views

What are the best algorithms for image segmentation tasks?

I recently started looking for networks that focus on image segmentation tasks related to biomedical applications. I could not miss the publication U-Net: Convolutional Networks for Biomedical Image ...
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0answers
9 views

Is there any time-varying directed graph dataset?

I am interested in the node classification task for graph data. So far,I've tried it with the Cora dataset, but it is an undirected graph and has word attributes as features. I want to extend this ...
1
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1answer
67 views

Neural networks for sports betting

I want to design a neural network that can be used for predicting sports scores for betting, specifically for American football. What I’d like to do is create a kind of profile for each game based on ...
2
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1answer
48 views

When and how to use a mix of loss functions for back-propagation?

I am trying to understand the best loss function to be used with a convolutional neural network. I came to know that we can mix two loss functions. Can any body share in what case was it done and how?
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2answers
78 views

What are the standard problems for CNNs and LSTMs?

What are the standard (or baseline) problems (or at least common ones) for CNNs and LSTMs? As an example, for a feed-forward neural net, a common problem is the XOR problem. Is there a standard ...
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1answer
74 views

Neural Network to estimate distance

I built a three layer neural network (first is 1D Convolutional and the remaining two are Linear). It takes an input of 5 angles in radians, and outputs two numbers from 0 to 1, which are respectively ...
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0answers
17 views

Computing layers dimensions for deep learning architectures

I have already a few projects in deep learning under my belt. However, there is one fundamental thing that has come to my mind recently while trying to implement my own architecture. Looking at the ...
3
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1answer
36 views

CNN how can i reduce gpu memory usage with large image sizes?

I am trying to train a cnn-lstm model, my sample image sizes are 640x640. I have a GTX 1080 ti 11GB. I am using Keras with tensorflow backend. Here is the model. ...
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0answers
40 views

CNN clasification model loss stuck at same value

I have CNN model to classify 2 classes. (Yes or No) I use categorical_crossentropy loss and softmax activation at the end. For input I use image with all 3 channels, for output I use One hot encoded ...
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0answers
59 views

What to do when an image classifier does good for a class but bad for another?

So I wrote a convolutional neural network for a binary image classification. I have around 5300 images for each class which I thought would be enough to at least give me a good accuracy on the ...
3
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1answer
43 views

Can a model, retrained on images classified previously by itself, increase its accuracy?

Let's assume I have a CNN model trained to categorize some objects on the images. By using this model I find more categorized images. If I now retrain this model on data set that consists old set and ...
3
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1answer
47 views

GPU/TPU acceleration for neural networks with various network topologies

I was thinking about different neural network topologies for some applications. However, I am not sure how this would affect the efficiency of hardware acceleration using GPU/TPU/some other chip. If, ...
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0answers
13 views

Numbers to image regression

I would like to create a machine learnig framework that could predict the 3D heat distribution of a room(of size 120x120x120) , given multiple parameters(position of the heater, orientation, power of ...
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0answers
24 views

How to get same accuracy with identical models in Keras and Tensorflow?

As we all know Keras backend uses Tensorflow and so it should give out same kind of results when we provide same parameters, hyper-parameters, weights and biases initialisation at each layer, but ...