Questions tagged [image-segmentation]
The image-segmentation tag has no usage guidance.
55
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5 views
How to generate fixed number of superpixels?
A lot of work regarding Graph Neural Networks require fixed number of nodes. In the case of image processing using graph, the image representation is often super pixels (like in this work https://...
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40 views
How do you deal with variable input sizes with an encoder-decoder net with skip connections in Keras?
I am currently getting into image segmentation with Keras, and I am using an encoder-decoder type as in the image below.
My problem is that applying a MaxPooling2D ...
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11 views
Loss function to compare non binary segmentation
I need to compare two images corresponding to landmark locations. I was thinking of something related to Dice loss. I cannot use dice loss since the image is not binary. The background is black but ...
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25 views
Tool for annotation of images for semantic segmentation
I have been searching around for a software tool, that I can use for annotating images. More specifically I want to do annotation to be used for semantic segmentation, meaning I want to create masks. ...
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24 views
Normalization of CT scans
I trained an infection segmentation models on a large dataset of CT scans, and want to extend it to other datasets to show the ability of the model to generalize. What I found though, is that CT scans ...
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20 views
Ways of calculating the area of colored regions in a map
Background
I am a PHD student trying to improve my data science. One of my research projects, has me tasked with determining the size of the clusters in a colored image of regions. Here is an example ...
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20 views
loss function for multi-label segmentation with class inbalance
In order to use a binary segmentation loss function in a multi label problem, I would like to permute the batch axis with the channel axis in the loss computation in order to compute the loss by ...
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8 views
How to Convolve a High-Res Image by a (fully convolutional) CNN kernel?
My CNN is an extremely simple neural network.
...
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13 views
IOU and dice_coef exceed 100% in multi task learning
Im doing a multi task learning for road and center line extraction (2 classes) I used IOU and dice_coef as a metrics :
...
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1answer
41 views
Extremely stochastic validation loss/accuracy
I am working on training DNNs on satellite data. The class distribution in the data is extremely imbalanced, so I train the neural networks using random majority undersampling to artificially balance ...
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1answer
68 views
How can I use my own dataset for Image segmentation using Tensorflow
I have a huge problem using my own created dataset for image segmentation using Tensorflow. The dataset that I've build contain images like the one shown below:
The problem that I have is: How do I ...
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1answer
37 views
For semantic sementation, why am I getting better loss values with binary cross entropy than dice coef?
I'm learning all related to data science and how to train U-Net to do semantic segmentation.
I have a U-NET with this loss function:
...
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15 views
Model selection Tensorflow for custom dataset comparing panoramic images vs regular images (Image segmentation)
I have a question regarding the use of a specific model such as Deeplab and how to create a custom dataset for it.
Background
To give a bit of background info, I want to compare panoramically stitched ...
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13 views
Why it is reshaped the last layers of VGG_UNet segmentation model?
I want to do a multiclass segmentation task using deep learning (in python). Here, is a summary of vgg_unet model that is mainly collected from GitHub. So, in my dataset 8 labels are available. So, at ...
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12 views
Is it possible to create a 3d to 2d U-net?
I was curious if it is possible to create a U-net type architecture that takes in a 3d image and outputs a 2d image? Or, alternatively, would some other architecture be better suited for this problem? ...
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1answer
9 views
Which colour channel from a TIFF image do I have to use?
I'm going to use the following dataset to do semantic segmentation with U-Net network.
LGG Segmentation Dataset
This dataset contains brain MR images together with manual FLAIR abnormality ...
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1answer
24 views
Multiple output size in neural network
In the paper "A NOVEL FOCAL TVERSKY LOSS FUNCTION WITH IMPROVED ATTENTIONU-NETFOR LESION SEGMENTATION" the author use deep supervision by outputing multiple outputmask which have different ...
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30 views
Why does dice coefficient equally weigh false positive and false negative?
According to this article:
Dice coefficient=
The 2-class DSC variant for class c is expressed in
Equation 1, where gic ā {0, 1} and pic ā [0, 1] represent the
ground truth label and the predicted ...
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40 views
Image segmentation network to extract questions from an image of a test paper?
This is the sample document ->
I want to extract questions along with the options. There are other question papers as which have questions with diagrams in them. I want to be able to extract them ...
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15 views
How to determine the decrease of resolution in per cent necessary for a partly blurred frame to appear sharp?
Given is a frame of a video taken with a lens focussing on the background, so the foreground is slightly blurred.
How to determine the decrease of resolution in per cent necessary for the blurred ...
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13 views
How to approach coarse-grained semantic segmentation?
Iām looking at doing something like semantic segmentation of images but where I only have pretty coarse-grained labels - roughly, for each 32x32 patch, I know if the answer should be āyesā, ānoā or ā...
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17 views
DICE loss too low but no overlap between prediction and label
I am trying to achieve the segmentation of the bone on the cross sectional area of MRI images with the Unet I found here. The label is a binary png image which I intend to compare to my prediction. ...
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36 views
How to deal with severe overfitting in a UNet Encoder/Decoder CNN in a task very similar to image translation?
I am trying to fit a UNet CNN to a task very similar to image to image translation. The input to the network is a binary matrix of size (64,256) and the output is of size (64,32). The columns ...
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221 views
Image Segmentation Class weight using tensorflow keras
I remember definitely being able to pass a list to class_weight with keras (binary image segmentation specifically). For example:
...
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7 views
Segmentation-free character recognition on an image: Multi-label, multi-class or sequential image classification problem?
I have some images which look like this one:
They exist of 3 possible characters (A-C) and a length of 4.
Now, I would like to run a neural network, which recognizes each character in the picture ...
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2answers
185 views
neural network probability output and loss function (example: dice loss)
A commonly loss function used for semantic segmentation is the dice loss function. (see the image below. It resume how I understand it)
Using it with a neural network, the output layer can yield ...
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38 views
What is the difference between proposal-based approach and proposal-free approach?
From here it says that
Techniques to solve instance segmentation can be roughly grouped into two categories: proposal-based methods and proposal-free methods. In proposal-based methods, a set of ...
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15 views
How to reduce the detection time in MaskRCNN
I've trained MaskRCNN in GPU instance and using the saved weight, I detected it in CPU instance based system. The detection time is taking too long.
...
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6 views
Refining segmentation masks using predictions of earlier frames
I am performing semantic segmentation. For that I have a dataset of videos in which every frame is labeled. Unfortunately, I don't know the order of the frames. That is why I am performing classic ...
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120 views
per class IOU & Jaccard Similarity in a Multiclass setting python
For a multiclass classification problem, How do you compute per class IOU ?
I am using the formula which is referenced/accepted in the below link
...
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1answer
72 views
Confusion matrix of UNET image sgemenation model
I have used Unet model for image segmentation. I have used RGB images and corresponding image masks and at output i got corresponding region of interest. Now i want to find confusion matrix of this ...
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9 views
Is it possible to find corresponding coordinates from a downsampled image?
Beforehand, I must apologize, I am just a beginner in image processing and I am not very familiar with many computer vision operations. Here is my problem:
I am using deep learning to perform a ...
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27 views
Drawing bounding rectangle around the tumor cv2
I am working on a project which predicts that the MRI has tumor or not, now the next step is to draw a bounding rectangle around the tumor. I want to extract the tumor from the MRI and bound the ...
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1answer
52 views
How to save multi-output predicted masks into two different folders after using model.predict_generator
I have a multi output segmentation task, the training process went well, but when Im trying to get the prediction I found difficulties to separate the two output into two different folders, in my ...
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1answer
26 views
how to compare two images and show the difference in a new image?
I want to compare two web pages images using computer vision techniques.
show what are non-unique portions comparing both images. which part image1 not exist in image2 vice versa.
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7 views
Multiple RoI per object of interest to train U-Net
I have determined RoI of image that contains an object (an organ on a CT-SCAN) that I wish to segment using a U-Net like network.
Should I train my network with the RoI I determined, or should I use ...
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19 views
Paragraph extraction from text
I am trying to separate scanned pages of a 3 column book into paragraphs. On the pages there can be images located in an arbitrary location, occupying part of one, two or all three of the columns.
...
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74 views
Is weighted jaccard metric suitable for semantic segmentation?
I'm trying to deal with a binary segmentation peoblem using Unet on Tensorflow 2.0 (Keras module).
My classes're higly unbalanced, so I have to use class weights (0.03 for background and 1.0 for ...
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1answer
19 views
Is it cheating to stratified sample the whole dataset based on a previous evaluation result?
I trained a model using a small mri dataset(57 patients).
The model's performance was so low(Train set 0.7, Val set 0.7, Test set 0.45).
I found the model segment tumor in upper part of brain well, ...
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1answer
140 views
How to prepare masks for multiclass semantic segmentation?
It's very straightforward for binary semantic segmentation: black color (0s) is responsible for background, whereas white color (1s) is responsible for objects of interest.
But what about multiclass ...
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21 views
Instance segmentation and scene reconstruction
I've been recently interested in various segmentation tasks especially instance segmentation. Having been experimenting with various different datasets I stumbled upon using the method for indoor ...
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25 views
Image segmentation for small images with rectangles
I am doing toy project and trying to make image segmentation for rectangles generated in small images. Here the code:
...
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1answer
95 views
Segmentation Network produces noisy output
I've implemented a SegNet and SegNet ReLU variant in PyTorch. I'm using it as a proof-of-concept for now, but what really bothers me is the noise produced by the network. With ADAM I seem to get ...
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15 views
Guidance required on image segmentation
I am new to deep learning. Specifically to image segmentation. I am trying to localise object from satellite images (screen grab from google maps). When I am going through articles/blogs in the ...
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1answer
37 views
What are features in computer vision?
I'm learning how U-NET network works to do semantic segmentation.
I think I have understood everything but features. What are those image features?
I read that convolutional layers extract features ...
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1answer
221 views
Patch wise training vs Full Convolutional Training in semantic segmentation
As mentioned in the title, what are those 2 methods? I already checked this question: Patchwise and Full training, (and the mentioned paper) but i can't really understand the meaning and the process ...
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123 views
Use of Active contour loss funtion in U-net
I am using a custom loss function named 'Active contour loss'.
I am getting an issue while segmentation. I have raised question for this on stack-overflow.
Can anyone please suggest some guidelines ...
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0answers
25 views
Video segmentation vs image segmentation
I am new to data science & working on a segmentation model, Basically I need to deploy this segmentation model in android devices using TensorFlow-Lite for real time camera frame segmentation.
I ...
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0answers
17 views
An CNN seems like capturing specific range of input data. (Image Segmentation)
I'm trying to build a model to segment brain tumors.
I trained a model, and the validation dice coefficient is disappointing(0.6). When i saw the predicted images with the ground truths, it seems ...
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0answers
15 views
Is there a way to test out simple filters before committing to coding them?
Is there a way to test out simple filters before committing to coding them?
Like if I want to estimate the feasibility of recognizing some features from images. Or to estimate the effort/...
