Questions tagged [semantic-segmentation]

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Why do we do need compression in Semantic Segmentation?

When doing semantic segmentation, we often make use of FCN, which can be thought of in two parts: an encoder and decoder. As I understand, the encoder compresses the image into a spatially small, but ...
Dude156's user avatar
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How can I use Artificial Intelligence to compare to paragraphs to see if they share the same meaning?

I am looking for a way to compare two paragraphs and see if both share the same meaning. For example, these two paragraphs have the same meaning, but they are worded differently. Paragraph 1: The ...
Jay's user avatar
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Batch Normalization Layer is not learning the data semantics of a dataset comprised of datasets from different sources

I have built a dataset for image segmentation that is comprised of datasets from several different sources. Almost all of my models have problems with learning the correct parameters of the ...
user199590's user avatar
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how to preprocess satellite imagery for semantic segmentation?

I have to train binary semantic segmentation in Python(using Tenforflow, rasterio, geopandas, sh). And I have raster .tif images and vector .shp images which is mask. I know that I should divide each ...
NailaBagir's user avatar
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How to compare word segmentation methods?

I am comparing a few methods of word segmentation in artificial language without dictionary and "golden" segmentation. Let's say, idolikecats is splitted ...
dobrowol's user avatar
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1 answer
177 views

What is Panoptic Segmentation?

In computer vision what is Panoptic Segmentation about? How it relates to Semantic Segmentation? and how it compares to Instance Segmentation?
Luca Anzalone's user avatar
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What does crop size refer to in DeepLabv3 paper?

In the paper in which DeepLabv3 is presented, the authors are mentioning that: "For atrous convolution with large rates to be effective, large crop size is required; otherwise, the filter ...
Manuel Maior's user avatar
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Resizing segmentation masks

I am trying to run a semantic segmentation model. The problem is, my data has different resolution for every image and for corresponding segmentation map (image and corresponding segmentation map ...
programmer_04_03's user avatar
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How to use UPSNet or Mask-RCNN? How to format image data for panoptic segmentation?

I want to use UPSNet (github repo) (paper) to train a model to perform panoptic segmentation on my own dataset. I would also consider using a model based on Mask-RCNN to simply perform instance ...
Sam K's user avatar
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How does mixing and matching encoders and decoders work in image segmentation?

I had a conceptual questions regarding architectures. I am using this git hub repository that allows one to quickly put together a segmentation pipeline. In reading the readme one thing that has me ...
TheCodeNovice's user avatar
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How to incorporate domain knowledge into a semantic segmentation network?

I'm working on a semantic segmentation project, and want to add some domain knowledge to the system. I want to ensure that for segmentation, there can only be one group of pixels that are predicted as ...
Mark-M2L's user avatar
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How to identify and diferentiate several edge lines of an object?

I want to create an AI to detect and identify certain edge lines on my image. The input image is a locker key, and I want to know the exact position of certain edges. Sample input image: Sample ...
Lluis C's user avatar
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Why CNN inference works on larger images

I have been reading up on 'regular' CNN's such as Mask R-CNN, and as far as I understand it they rely on a fully connected layer in the end to classify pixels. FCN's (such as U-Net) which do not use ...
Cartman123's user avatar
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How does the classification head of EfficientDet work?

EfficientDet outputs classes and bounding boxes. My question is about both but specifically I am interested in the class prediction net part. In the paper's diagram it shows 2 conv layers. I don't ...
ML Dev's user avatar
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How to re-train an AI model to have smaller input image size

I need a PyTorch Model which can do road segmentation on OAK-D camera. The model provided requires Input Image Size: 896x512, which is too big for running on OAK-D camera. Thus I need to re-train it ...
Franva's user avatar
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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 ...
Talha Anwar's user avatar
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483 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 a python pillow. <...
Eka's user avatar
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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 ...
brethvoice's user avatar
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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-...
ElectricMinimum58's user avatar
1 vote
0 answers
67 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 ...
Nuwanda's user avatar
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4 votes
1 answer
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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 ...
dato nefaridze's user avatar
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1 answer
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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 ...
Izzo's user avatar
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2 votes
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823 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 ...
147956's user avatar
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1 answer
333 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 ...
Skyris's user avatar
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1 answer
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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 ...
miimi's user avatar
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1 vote
1 answer
125 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 ...
Bert Gayus's user avatar
3 votes
3 answers
680 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 ...
cmed123's user avatar
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