Questions tagged [image-segmentation]

For questions related to image segmentation (in computer vision and related AI fields).

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3
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1answer
6k views

What is a fully convolution network?

I was surveying some literature related to Fully Convolutional Networks and came across the following phrase, A fully convolutional network is achieved by replacing the parameter-rich fully ...
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0answers
20 views

Super-Resolution with Convolutional Neuronal Networks, why interpolation at the beginning?

I have read several papers about super-resolution with CNNs, where a low-resolution image is reconstructed to a high-resolution image. What I don't understand is, why it is necessary to interpolate ...
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0answers
233 views

what will be the best loss function for unet to predict the each pixel values?

I'm predicting the used 9 pictures to predict the last picture so (40,40,9) -> unet -> (40,40,1) but as you see the predict picture It's not just a mask(0or 1) its float so which loss function ...
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1answer
25 views

How to create vector representation of roadmap like scans

What would be the best way to create a vector representation of roadmap like scans? The goal I am trying to achieve is illustrated below. The left side represents the source image, the right side the ...
0
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1answer
51 views

How to use 'Canny/Watershed' algorithm's output as an input for Image Classification Model

I have a very silly problem in hand. I have implemented 2 methods which give me the mask to separate the objects from the background. What I get from one method is the object encapsulated in the red ...
3
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1answer
43 views

Can neural network help me with detecting center coordinates of particles in an image?

I have an image of some nano particles that was taken with Scanning Electron Microscope (SEM) attached here. I want to obtain center points coordinates (x,y) for each particle. Doing it by hand is ...
2
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1answer
2k views

What are some good alternatives to U-Net for biomedical image segmentation?

Soon I will be working on biomedical image segmentation (microscopy images). There will be a small amount of data (a few dozens at best). Is there a neural network, that can compete with U-Net, in ...
1
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1answer
61 views

How do I generate a feature representation of a saliency map (or mask)?

Generally, CNNs are used to extract feature representations of an image. I'm right now dealing with the class of CNN that produces saliency maps, which are generally in the format of a mask. I'm ...
2
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0answers
37 views

Tversky Loss paper implementation: Recall/Precision do not improve as stated

I have been trying to implement this paper and I am very much intrigued. I am working on a medical image problem where I have to segment very small specimens on Whole Slide Images (gigapixel ...
2
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0answers
25 views

What are the current tools and techniques for image segmentation in order of pragmatism?

To explain what I mean I'll depict the two extremes and something in the middle. 1) Most pragmatic: If you need to just segment a few images for a design project, forget AI. Go into Adobe Photoshop ...
2
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0answers
128 views

What is the difference between using a backbone architecture and transfer learning?

I'm super new to deep learning and computer vision, so this question may sound dumb. In this link (https://github.com/GeorgeSeif/Semantic-Segmentation-Suite), there are pre-trained models (e.g., ...
2
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1answer
175 views

What make a CNN suitable for image classification or for semantic segmentation?

I've just started with CNN and there is something that I haven't understood yet: How do you "ask" a network: "classify me these images" or "do semantic segmentation"? I think it must be something on ...
2
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1answer
107 views

Why everyone is using CNN for image segmentation?

I'm a newbie in artificial intelligence. I have started to research how to do image segmentation and all the papers that I have found are about CNN. Most of them use the same network, U-net, but with ...
2
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1answer
51 views

How many ways are there to perform image segmentation?

I'm new in Artificial Intelligence and I want to do image segmentation. Searching I have found these ways Digital image processing (I have read it in this book: Digital Image Processing, 4th edition)...
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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 ...
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0answers
315 views

Find the nearest object in a image which is captured from camera?

Objective : To find the nearest object (closer distance object) in the single camera image. But Image Contains multiple objects shown below: I searched in the net and found this formula to ...
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0answers
33 views

How to train image segmentation task with only one class?

Is there a neural network that has architecture optimizations for segmenting only one class (object and background)? I have tried U-net but it is not providing good enough results. I am wondering if ...
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0answers
44 views

Using U-NET for image semantic segmentation

I'm getting literally crazy trying to understand how U-NET works. Maybe it is very easy, but I'm stuck (and I have a terrible headache). So, I need your help. I'm going to segment MRI to find white ...
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0answers
57 views

How to extract face details from a image

I am trying to make a face login application that authenticates the user when matching the registered face and the given face. currently, the issue is I cant extract the face descriptions from the ...
9
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1answer
2k views

Deep learning for bitmap tracing: extract simple svg paths from bitmaps

I need an algorithm to trace simple bitmaps which only contain paths with a given stroke width. It is obviously very easy to generate bitmaps from vector paths, so creating data for a machine ...
2
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1answer
53 views

What are some references that describe known filters (or kernels) and how we can create new ones?

I'm pursuing a master's degree in Artificial Intelligence. My final work is about Convolutional Neural Networks. I was looking for information about filters (or kernels) of the convolutional layers. I ...
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0answers
37 views

How can I improve the performance of a model trained to detect vehicle poses?

I'm looking for some suggestions on how to improve our vehicle image recognition. We have an online marketplace where customers submit photos of their vehicles. The photos need to meet certain ...
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1answer
100 views

Best approach for 2D Grid Image Segmentation

I'm working on a project where I need to extract text from grocery discount flyers like the Costco announcement below (retrieved in a random google search, Costco is not the deal here): If I just run ...
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0answers
32 views

How to measure the size of an crack which is segmented from an image using Mask-RCNN?

I am a masters student going to work in a project to analyze the cracks in underwater concrete structures. I need some suggestions for data acquisition and length measurement of the crack. I have ...
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0answers
210 views

creating your own dataset similar to cityscapes format

I'm trying to train a neural network with my own dataset. The neural network can accept the cityscape format. Is there any application that can give mask/segmented image, instance image, label IDs ...
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0answers
20 views

Segmentation of a static object in a video

I've videos from a mounted camera on a helmet and the manually segmented labels (mask) of them. The mask is valid through the entire video, only the scene vary. In different videos the camera is ...
5
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1answer
68 views

Do models train better if the labelling information is more specific (or dense)?

I'm working on a project where there is a limited dataset of videos (about 200). We want to train a model that can detect a single class in the videos. That class can be of multiple different types of ...
4
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2answers
125 views

What are the best algorithms for image segmentation tasks?

I recently started looking for networks that focus on image segmentation tasks related to biomedical applications. I could not miss the publication U-Net: Convolutional Networks for Biomedical Image ...
2
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0answers
74 views

Is there a deep learning-based architecture for digit localisation?

I'm new to object detectors and segmentation. I want to localize digits on a plate as fast as possible. All images of the dataset are normalized to $300 \times 60$. There are different approaches to ...
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0answers
24 views

Resizing effects on image recognition

I have been building a multilabel image classification model using inception v3, which uses images of size 299x299, I have been wondering what are the effects of feeding images of rectangular shapes ...
2
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1answer
164 views

“Outside-in” versus “Inside-out” machine learning

A little background... I’ve been on-and-off learning about data science for around a year or so, however, I started thinking about artificial intelligence a few years ago. I have a cursory ...
2
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0answers
28 views

Confidence Maps and Non-Linearity

I am currently trying to improve a CNN architecture that was proposed for generating depth images. The architecture was originally proposed for autonomous driving and it looks like following : The ...
4
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1answer
911 views

What do the words “coarse” and “fine” mean in the context of computer vision?

I was reading the well know paper Fully Convolutional Networks for Semantic Segmentation, and, throughout the whole paper, they talk use the term fine and coarse. I was wondering what they mean. The ...
4
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0answers
36 views

What are some neural network models that can use auxiliary info during training for image segmentation?

What are some deep learning models that can use supplementary information other than RGB channels for image segmentation? For example imagine a poorly shot image of a river (blue) that shows a gap, ...
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0answers
33 views

Which model to use when selecting objects of interest?

I have a set of polygons for each image. Those polygons consist of four $x$ and $y$ coordinates. For each image, I need to extract the ones of interest. This could be formulated as an Image ...
2
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1answer
110 views

How to add some data input in a CNN?

There is this problem I have encountered, I was trying to classify the pixels from input image into classes, sort of like segmentation, using a encoder-decoder CNN. The “interested” pixels usually ...
3
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2answers
600 views

Which evaluation methods can I use for image segmentation?

I implemented an image segmentation pipeline and I trained it on the DICOM dataset. I compared the results of the model with manual segmentation to find the accuracy. Is there other methods for ...
1
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1answer
112 views

How do I segment each part of a DICOM image?

As I'm beginner in image processing, I am having difficulty in segmenting all the parts in DICOM image. Currently, I'm applying watershed algorithm, but it segments only that part that has tumour. ...
0
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1answer
135 views

How to give each segment a new colour in image segmentation? [closed]

I'm currently working on a tumour detection project using Dicom images. As I'm a beginner, I don't know how to segment each part in the image and give each segment a new different colour. I'm using ...
24
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5answers
27k views

How can I deal with images of variable dimensions when doing image segmentation?

I'm facing the problem of having images of different dimensions as inputs in a segmentation task. Note that the images do not even have the same aspect ratio. One common approach that I found in ...

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