Questions tagged [semantic-segmentation]

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Understanding last convolution of U-NET for image segmentation

I was trying to understand the last layer of Image segmentation architecture (U-NET). For example what will be the logits-probability distribution of pixels in each case? I know that its there as ...
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22 views

Image segmentation with U-net

I am trying to understand if Semantic segmentation with U-NET. Are we training kernels to extract features or are we training a fully connected layer at the end? Or both? If so, how are we training ...
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1answer
23 views

Remove frame from background

I am having 400 images that look like the following: I would like to remove the frame and only get the image in the middle: I tried the MODNet model ...
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1answer
11 views

How do you train a semantic segmentation model to optimize for IoU rather than accuracy?

I am currently building a U-NET semantic segmentation model on Tensorflow Keras to classify pixels as belonging to or not belonging to a class. For this problem, I've isolated the masks for only one ...
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Instance segmentation - Which is the best approach for my use case?

I am looking to train an instance segmentation model that will be running on the edge, like on mobile devices. What is the best network (Mask RCNN, DeepLab v2/3 etc.) for this use case? Which gives ...
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1answer
91 views

Why is my training loss not changing?

I'm trying to train a semantic segmentation model based on this architecture, using this one as a base. The base model uses about 10 ReLU activations, and when implemented according to the first paper,...
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14 views

What is the best Panoptic Segmentation algorithm up to date?

A Cityscapes ranking would suggest that EfficientPS and Panoptic-Deeplab are the best, while the Coco ranking suggests other algorithms, more recent, like mask2former. Which one is the best?
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1answer
20 views

Is there an official procedure to compute mIoU?

Although it sounds silly, I'm not finding an official source to compute mIoU. I'm realizing a semantic segmentation task, and I want to compute the mIoU over a dataset. My doubt is, should I compute ...
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9 views

Increasing training accuracy of U-Net segmentation model

I was working with segmentation using u-net and MobileNet. While I trained with input size 256*256 it had an output with Val loss: 0.044 (In this time dense layer was 256, 128, 64, 32 with a learning ...
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1answer
53 views

resnet50 implementation for semantic segmentation

I am new to resnet models. I want to implement a resnet50 model for semantic segmentation I am following the code from this video, but my numclasses is 21. I have a few questions: If i pass in any ...
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8 views

Browser history segmentation

I'm trying to segment a browser history into semantically coherent sessions. For example, a user might be working on a school project for 30 minutes, then planning an upcoming vacation for 30 minutes, ...
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Why my encoder-decoder based segmentation model is producing high loss, when UNet/SegNet is working fine

I have got a UNet and SegNet model implemented on a dataset, with high mean-IoU and accuracy. Now I tried to implement SegNet(not FCN, just encoder-decoder portion) on the same dataset. But for this ...
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90 views

The channel dimension of the inputs should be defined. Found `None`

Hello I'm trying to use SegNet in my project with tensorflow, for educational purpose. And I'm surely following someone else's code on GitHub: ...
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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 ...
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34 views

Pre-trained models for semantic segmentation of satellite images

I'd like to use semantic segmentation of satellite images but I don't have the processing power to train existing models or producing one my own. Ideally, I'm looking for a U-Net CNN model that can be ...
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19 views

Model comparison: how to explain worse (lower) dice scores but better (lower) Hausdorff distances

I have two segmentation models (U-Net-like architectures): an original model, and an experimental model. I use the dice score and 95% Hausdorff distance to evaluate their performance. Using the first ...
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1answer
48 views

My semantic segmentation model classifies everything as background

So, I am working on a semantic segmentation task using U-Net. The dataset is very unbalanced, with the background being by far the most common, and the last class being very scarce. First I trained it ...
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34 views

PyTorch fcn_resnet50: Inconsistent segmentation performance in training and evaluation

Although fcn_resnet50 is shown to perform well in pytorch examples and tutorials, the performance on my end tells a different story in training. fcn_resnet50 segments relatively poorly in training, ...
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1answer
16 views

Suitable instance counting CNN for training on polygonal masks

I have a medical dataset labeled with polygonal masks (rather than rectangle boxes). It works well for pixel annotation with UNet to generate masks of healthy vs damaged skin. Now I need to do ...
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28 views

Region Growth custom seed points

I've coded the 3D Region Growing from PCL to Python, thanks to the pseudo code from : https://pcl.readthedocs.io/projects/tutorials/en/latest/region_growing_segmentation.html But I had a question, ...
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2answers
244 views

High image segmentation metrics after training but poor results in prediction

I'm trying to build a model with Keras that predicts four classes of features from microscopy noisy images which cover about 10 - 30 % of the image. I'm using U-net because my dataset is small (150 ...
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1answer
38 views

Criteria for saving best model during training neural network?

I am doing 4-class semantic segmentation with U-net using generalised dice loss as loss function. General approach to save best model during training is to monitor validation loss at each epoch and ...
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8 views

Proper loss for multiclass 2D segmentation with coarse masks

Trying to figure out which is the proper loss for the task that has: High dimensional grayscale images with relatively small coarse annotated masks With a high imbalance in classes, as bg is x100 ...
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1answer
30 views

Pixel labelled image is must for semantic segmentation using deep learning in matlab?

I have large set of CT images containing lung regions. But I don't have corrosponding pixel labelled images. So how I could do semantic segmentation using DL in matlab. Like a test program I created 6 ...
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1answer
49 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 ...
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145 views

How to convert RGB to One Hot encoding of Pixel in Pascal VOC Dataset?

I am trying to implement Semantic Segmentation on PASCAL VOC 2007 Dataset using Fully Convolutional Network. My Network outputs images of (Height, Width, Classes); but the training label masks are of ...
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1answer
86 views

Multiclass semantic segmentation with some classes possibly not present in some of the images

Let's assume we have a large annotated dataset with 4 classes. In this dataset, there might be annotated images with less than 4 classes, where the remaining classes might or might not be present. As ...
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78 views

What is the difference in computational cost at inference time between object detection and semantic segmentation?

I am aware that YOLO (v1-5) is a real-time object detection model with moderately good overall prediction performance. I know that UNet and variants are efficient semantic segmentation models that are ...
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1answer
37 views

Which F1-score is used for the semantic segmentation tasks?

I read some papers about state-of-the-art semantic segmentation models and in all of them, authors use for comparison F1-score metric, but they did not write whether they use the "micro" or &...
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14 views

What is the right loss function for semantic segmentation or do I have to use all of them?

I'm doing my PhD research about image semantic segmentation and now I'm trying to understand what kind of loss function do I have to use with a CNN like U-Net. I have found the paper "A survey of ...
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1answer
270 views

Semantic segmentation of an image with multiple labels per pixel

I am building a model for a multiclass sematic segmentation of a skin disease. At a moment I am using U-Net for binary classifications. In this multiclass problem I have the following cases. There are ...
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19 views

Utilizing 1x1(x1) convolutions as a learned max pooling (3D)?

I have a semantic segmentation network that ingests 3D images (hyperspectral $(x, y, b)$) and predicts 2D images (semantic map $(x, y)$). This network takes the form of a classic UNet, though it ...
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32 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 ...
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1answer
1k views

What is Deep supervision?

I'm interested in segmentation models for medical imaging purposes. When I looked at the state of the art, I fell on a paper on a new architecture, Unet++: UNet++: A Nested U-Net Architecture for ...
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1answer
123 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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78 views

Image segmentation with large class imbalance leads to zero precision/recall

I have a binary semantic image classification problem where only very small parts of the images are positive, most of it is negative. In the training data I have a positive rate of around 0.023, which ...
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2answers
61 views

How to extract contents by topic from a document?

I am trying to extract information from resumes. I tried the pdfminer for the text extraction. But I need to extract the contents from a resume with respect to its title. For example: I will be giving ...
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1answer
29 views

Semantic networks: word2vec?

I have some doubts on how to represent the relationships between words in texts. Let’s suppose I have two sentences like these: ...
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1answer
68 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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18 views

How to approach coarse-grained semantic segmentation?

I’m 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 “yes”, “no” or “...