Questions tagged [semantic-segmentation]

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What to do when model stops learning after some epochs

I am training a segmentation model on 3D data, after around 170 epochs which took around 4 days, I notice the model is no more learning and the dice score is at 0.51. What is the best approach at this ...
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1answer
16 views

Dissection of a depth map

I am curious about how depth maps work. While searching I came across this website which contains some images and their depth maps. I took this depth map and tried to study it using python pillow. <...
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2answers
41 views

What is the difference (if any) between semantic segmentation and multi-class, mutually exclusive classification?

Multi-class classification is simply assigning all data points into one of up to any finite number of mutually exclusive labels. I am new to the field(s) of AI/ML and I keep hearing people use the ...
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21 views

What is meant by Hinton when he refers to “Part-Whole Hierarchies” in his GLOM framework

I was recently reading Hinton's GLOM idea How to represent part-whole hierarchies in a neural network, and I am simply unsure about what exactly he means when he says parsing images into "part-...
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22 views

Why does my model only predict 1s or 0s in multiclass segmentation?

I am currently trying to train a UNet model on the dronedeploy segmentation dataset. My problem is that I only get outputs like this from my model: This means that in the output maps I only get 0s ...
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20 views

Pixel values of segmap in multi-class semantic segmentation

I'm preparing a dataset for a multiclass semantic segmentation using U-Net like architecture. To be precise, I've got it ready but a question came to my mind. How does pixel values of a segmentation ...
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1answer
35 views

How does Mask R-CNN automatically output a different number of objects on the image?

Recently, I was reading Pytorch's official tutorial about Mask R-CNN. When I run the code on colab, it turned out that it automatically outputs a different number of channels during prediction. If the ...
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1answer
60 views

What does the “number of channels” correspond to in U-Net?

I'm studying the U-Net CNN architecture. I'm new to CNNs and am confused regarding the "number of channels". Referring to the U-Net diagram, the input image is convolved with a 3x3 mask ...
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72 views

Semantic segmentation - background or ignore for non-target classes?

I am training a deep learning model for semantic segmentation. I am using the cityscapes dataset for training/evaluation. In cityscapes, there are 34 classes, and of which, we consider only 19 classes ...
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1answer
29 views

How should I incorporate numerical and categorical data as part of the inputs to the U-net for semantic segmentation?

I am using a U-Net to segment cancer cells in images of patients' arms. I would like to add patient data to it in order to see if it is possible to enhance the segmentation (patient data comes in the ...
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24 views

How a Superpixel Pooling Layer can be used for image segmentation?

The concept of Superpixel Pooling Layer can be found in the paper "Weakly Supervised Semantic Segmentation Using Superpixel Pooling Network". The general idea of superpixel pooling is very ...
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15 views

Instance Segmentation Using A Semantic Segmentation Map and Class-Wise Bounding Boxes

Is it possible to perform instance segmentation if you have the following: Binary Segmentation Map Bounding Boxes (with respective class) Let's say we're doing something within cellular microscopy ...
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1answer
22 views

What are the state-of-the-art Person-Detektion / Human-Segmentation?

I would like to use a deep learning approach to detect people in videos. I have found some freely accessible implementations like Human Segementation with Pytorch or BodyPix / DeepLab / Pixellib with ...
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22 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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1answer
47 views

Why does my model not improve when training with mini-batch gradient descent, while it does with Adam?

I am currently experimenting with the U-Net. I am doing semantic segmentation on the 2018 Data Science Bowl dataset from Kaggle without any data augmentation. In my experiments, I am trying different ...
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3answers
156 views

If I trained a model to perform semantic segmentation on images with only one object, would it also work on images with multiple objects?

I'm working on semantic segmentation tasks in the medical space using the U-Net. Let's say that I train a U-Net model on medical images with the goal of segmenting out, say, ligaments, from a medical ...