Questions tagged [image-segmentation]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
0
votes
1answer
15 views

Segmentation 3D Unet checkerboard artifacts in slices above and below segmentation voxels

I suppose an image is worth too many words, so here is the image: As you can see, in the middle where there are voxels to be segmented, no artifacts are present. Whereas on the top and bottom I get a ...
0
votes
0answers
10 views

Clustering 3D image voxels based on their location and value

My goal is to detect whether a MRI image contains an anomaly and the location of the anomaly. In my dataset I have MRI brain images which contain values of electrical conductivity of brain tissues. ...
0
votes
0answers
28 views

image segmentation with cityscapes dataset

I am a beginner in image segmentation. I have the train, test and valid folder from a cityscapes dataset as ...
1
vote
0answers
17 views

Lovasz Softmax loss explanation

I would like to use Lovasz softmax for foreground background semantic segmentation because of its ability to improve segmentation with Jaccard index according to paper. I got the idea that its a ...
0
votes
0answers
9 views

Can i segment/crop out image using image processing?

I have a large dataset of bottles. I want to train a model with this dataset. But before feeding the input images to the model I want to crop out the bottle from the background. Is there a way to do ...
0
votes
0answers
7 views

What is the input to CNN in this image segmentation paper?

I am doing a project on polyp segmentation in colonoscopy images. I have recently read the paper Polyp-Net: A Multi-model Fusion Network for Polyp Segmentation provided here. I have a few question ...
0
votes
0answers
31 views

finding the defect button

In case of a project where you are going to detect whether the image printed on a button is correct or not and given that you have only a one correct possibility of a correct image and some incorrect ...
0
votes
0answers
7 views

Attention block versus residual block in U-net architecture?

I work on a project and I intend to use autoencoder (U-net) for my problem, based on the research that I've conducted, some authors used the recurrent residual U-net but I intend to use new approaches ...
0
votes
0answers
12 views

Should training and validation patches come from different images/files for image segmentation

In the situation where we have an image segmentation problem and we feed patches (smaller parts of the images) to the model, should the training and validation patches come from different files (...
0
votes
0answers
9 views

Can Dice Similarity index be higher than Jaccard index (Mean IOU) for a segmentation task? If so why does this happen?

I am currently doing a segmentation task. DICE is 0.94 and Mean IOU (Jaccard Index) is 0.63. How can mean IOU be lesser than DICE and is this possible. Also need explanations on scenarios where ...
0
votes
1answer
24 views

Hook up PyTorch U-Net model to video

I built a U-Net model in PyTorch that is trained on medical images to detect polyps. The purpose of the model is to do semantic segmentation, so it must predict the location + class of polyps. Now I ...
0
votes
0answers
11 views

Detection of vortex and numbering on basis of rotation

Problem Statement: I have a video of ANSYS Simulation of vortices formed due to flat plate plunging. The video contains vortices (in simpler terms blobs), which are distinguished according to their ...
0
votes
0answers
26 views

Computing symmetric difference hypothesis divergence $H \Delta H$ for two domains using a segmentation network

Given two domains $D_1$ and $D_2$, the symmetric difference hypothesis divergence ($H \Delta H$) is used as a measure how much two domains differ from each other. Let the hypothesis, segmentation ...
1
vote
1answer
26 views

How to design a model for contour recognition? In particular, how to shape the output layer?

I want to design and train a neural network for the automatic recognition of the edges, in some microscopic images. I am using Keras for a start, I may consider PyTorch later. The structure of the ...
0
votes
0answers
7 views

How to check if 2 images where splitted?

There is an original data-set of images. Each image was splitted into 2 parts (left-right). I want to run on all those splitted images and check if each 2 images are spliited from same image. Is ...
2
votes
0answers
25 views

Instance Segmentation using the predefined bounding boxes

I want to do Instance Segmentation using the images in my dataset which are already annotated and I don't want to train the model but use the pre-trained model. I was following this colab notebook. ...
2
votes
1answer
19 views

Segmentation model to predict face forward and profile parts of the face

I am developing a model for feature counting on a person's face that consumes three photos (one face forward and two profile pictures). My model can already detect features, but it counts some ...
1
vote
1answer
72 views

How to resize image along with their mask?

I have original images of the size 1935x1481. I am using labelme to annotate the images. I am creating polygons on the original image. Is there a way to resize the image along with their mask? I am ...
1
vote
1answer
25 views

Why do we need to concatenate in a U-Net?

You might be familiar with the U-Net, a machine learning network deceived for image segmentation. It's basically an encoder/decoder network with some direct links between encoder and decoder segments: ...
1
vote
0answers
26 views

Beginner level: how to interpret LIME and classification result

I am new to the concept of model interpretability using LIME method. I am following the tutorial LIME for spectrogram classification. I am finding hard to understand the color coding -- before using ...
2
votes
0answers
26 views

Transfer Deep Learning from one aerial imagery datset to many others

I am new to Deep Learning but have been able to use RasterVision successfully to predict building footprints within a set of aerial imagery. This aerial imagery data set is for a province of New ...
1
vote
1answer
41 views

Correct way of computing dice score for image segmentation?

In binary image segmentation, for given a set of images, it's true mask and predicted mask. How do you compute dice score? Should I compute the dice score for each image separately and then find mean ...
0
votes
0answers
31 views

How to use mean IoU for RGB mask (keras implementation)?

I am training pix2pix GAN for converting SAR satellite images to segmentation mask. But I am not aware about how to use the mean IoU to evaluate my model. My output is of ...
0
votes
0answers
58 views

Best algorithm for real-time instance segmentation in videos?

I want to do object detection in real-time (meaning localization and classification) on videos (25 FPS), but with the added constraint that my training data is labelled using binary masks, rather than ...
1
vote
1answer
28 views

3 images as one input in CNN (U-Net) [closed]

I have been advised by my supervisor that if my U-Net segmentation network has RGB images at the input then I could use the channels for different images - median filter for R, normalization for G, ...
1
vote
1answer
424 views

How can I create .nii (nifti) file from 3D Numpy array

I have a prediction numpy array. How can I make a .nii or .nii.gz mask file from the array?
1
vote
1answer
69 views

Modifying U-Net implementation for smaller image size

I'm implementing the U-Net model per the published paper here. This is my model so far: ...
0
votes
0answers
17 views

U-Net doesn't work with images different from the dataset

I have implemented a very similar U-Net code from github, but for a different dataset, this one, to segment roads, it works fine using the test folder images, but when i for example, pick a print from ...
1
vote
1answer
32 views

Implementing U-Net segmentation model without padding

I'm trying to implement the U-Net CNN as per the published paper here. I've followed the paper architecture as closely as possible but I'm hitting an error when trying to carry out the first ...
0
votes
0answers
10 views

Instance segmentation mask creation for adjacent objects within the same class

How are instance segmentation masks created for adjacent objects from the same class ? If for example we have different objects, we can distinguish between them using the labels, but how to ...
0
votes
0answers
8 views

Boundary segmentation

I have one problem regarding segmentation. I would like to put more concentration on the boundary instead of the interior of segmented part. Is that possible to do using Tensorflow 2? For example, if ...
0
votes
1answer
26 views

Semantic segmentation in high-resolution images with high variance - cannot avoid underfitting

I am working on a dataset of 2K images for a semantic segmentation problem. I want to detect and localize small objects, with the smallest mask to be 5x5 pixels. The images include 5 different ...
1
vote
1answer
182 views

Creating parallel keras layers

I am new to Keras and ML and I want to create a NN that can seperate a bitmap-like image into its visual components. My approach is to feed a two dimensional image (lets say 8 by 8 pixels) into a NN, ...
1
vote
1answer
24 views

Photorealistic synthetic data for object segmentation

Let's say that we have a very small labelled dataset for instance segmentation and there is a photorealistic physics engine available that can produce synthetic data for us. Looking on the web I haven'...
0
votes
0answers
22 views

Changing order of input dimension in Tensorflow 3-D Layers

According to the official documentation of tf.keras.layers.Conv3D 5+D tensor with shape: batch_shape + (channels, conv_dim1, conv_dim2, conv_dim3) if data_format='channels_first' or 5+D tensor with ...
1
vote
1answer
90 views

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 ...
0
votes
0answers
56 views

Agglomerative Hierarchical Clustering on Images

My goal is to implement the agglomerative hierarchical clustering algorithm on an RGB image to cluster every pixel until some stopping criteria is reached. In order to do so, I assumed that each pixel ...
1
vote
0answers
20 views

Semantic segmentation to instance segmentation

Having a mask from semantic segmentation I want to split it to list of non-overlapping instances masks(like an output from instance segmentation). Do you know some fast algorithm, approach, tool or ...
1
vote
1answer
25 views

What do the parameters used in crop mean?

When we have an image to be used as an input to a CNN and we want to classify only part of the image, we usually feed the classifier with a crop of the image. Lets say my image is called frame and <...
0
votes
0answers
13 views

I have no access to gpu due to usage limits?

I start running my code using google colab I first set the execution to GPU and then I run my code for a training task using keras !after 1 hour I got a message saying I can't use GPU due to usage ...
0
votes
0answers
164 views

Implementing Multiclass Dice Loss Function

I am doing multi class segmentation using UNet. My input to the model is HxWxC and my output is, ...
0
votes
0answers
15 views

Satellite Change Segmentation using Unet

Hi StackExchange community I am working on to train a Unet for satellite change segmentation. My dataset consists of images(before change),images(after change) and the corresponding change ...
0
votes
0answers
13 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://...
1
vote
0answers
105 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 ...
0
votes
0answers
19 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 ...
3
votes
1answer
108 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. ...
1
vote
1answer
274 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 ...
1
vote
1answer
41 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 ...
1
vote
1answer
138 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 ...
1
vote
1answer
502 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 ...