All Questions
Tagged with convolutional-neural-networks image-segmentation
43 questions
34
votes
5
answers
43k
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 ...
- 607
20
votes
1
answer
37k
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 ...
- 335
5
votes
1
answer
105
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 ...
- 153
4
votes
1
answer
4k
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 ...
- 211
4
votes
2
answers
296
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 ...
- 41
4
votes
1
answer
6k
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 ...
- 41
4
votes
0
answers
57
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, ...
- 41
3
votes
1
answer
233
views
What is the use of the regular convolutional layer in expansion path of U-Net?
I was going through the paper on U-Net. U-net consists of a contracting path followed by an expanding path. Both the paths use a regular convolutional layer. I understand the use of convolutional ...
- 404
3
votes
1
answer
671
views
How to incorporate a symmetry constraint in the loss function to train a CNN?
I have a task of extremely sparse binary segmentation, i.e. the segmentation mask contains either 0 or 1, and there are ~95% zeros and only ~5% ones. I use the focal loss to address the sparseness (...
- 188
3
votes
1
answer
72
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 ...
- 31
3
votes
1
answer
438
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 ...
- 33
3
votes
2
answers
294
views
Is such a captcha AI-resistant?
Let's say we have a captcha system that consists of a greyscale picture (of a part of a street or something akin to re-captcha), divided into 9 blocks, with 2 missing pieces.
You need to choose the ...
user38359
2
votes
1
answer
66
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 ...
- 493
2
votes
1
answer
214
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 ...
- 493
2
votes
1
answer
94
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)...
- 493
2
votes
1
answer
215
views
How can I tell a CNN to ignore nodata values in satellite images?
I'm trying to train an image segmentation model on satellite images. There are two main issues: first, not all of the images are the same size. My understanding is that by using a fully convolutional ...
- 21
2
votes
1
answer
147
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 ...
- 21
2
votes
0
answers
299
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., ...
- 21
2
votes
0
answers
224
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 ...
- 129
2
votes
0
answers
214
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 ...
- 121
1
vote
1
answer
385
views
What make a CNN suitable for image classification or semantic segmentation? [closed]
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 ...
- 493
1
vote
1
answer
231
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 ...
- 111
1
vote
1
answer
118
views
How to quickly change hand-drawn shapes to symmetrical polished shapes?
Given a hand-drawn shape, I'd like to generate the corresponding symmetrical polished shapes such as circle, rectangle, triangle, trapezoid, square, parallelogram, etc.
A short video demonstration
...
- 121
1
vote
1
answer
118
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 ...
- 317
1
vote
0
answers
67
views
Visualization of Transposed Convolutions
After reading on Transposed Convolutions and Fully Convolutional Networks in the d2l book (14.10 and 14.11), I wondered about the visualization of transposed convolutions.
As you probably know, ...
- 153
1
vote
0
answers
30
views
Latest status on stability of CNN architectures to noise and "clever hans" issues
I was working with CNN architectures for image segmentation a few years ago, and I remember there was a big concern about on the stability of the predicted masks due to the introduction of small ...
- 207
1
vote
0
answers
146
views
Training a CNN for semantic segmentation of large 4600x4600px images
I am trying to implement a CNN (U-Net) for semantic segmentation of similar large grayscale ~4600x4600px medical images. The area I want to segment is the empty space (gap) between a round object in ...
- 11
1
vote
0
answers
25
views
Model output segmentation maps which are not full
I created a VGG based U-Net in order to perform image segmentation task on yeast cells images obtained by a microscope.
There are a couple of problems with the data:
There is inhomogeneity in the ...
- 188
1
vote
0
answers
90
views
Extending patch based image classification into image classification
I am trying to classify tampered, pristine images from set of images, in that I have built a network in which I would divide the image into multiple overlapping patches and then classify them into ...
- 21
1
vote
0
answers
97
views
How can the FCNN reduce the dimensions of the input from $1048 \times 100$ to $523 \times 100$ with max-pooling?
I am trying to implement a paper on Image tempering detection and localization, the paper is Image Manipulation Detection and Localization Based on the Dual-Domain Convolutional Neural Networks, I was ...
- 21
1
vote
0
answers
225
views
Suppress heatmap non-maxima in segmentation with UNet
I'm using U-Net for image segmentation.
The model was trained with images that could contain up to 4 different classes. The train classes are never overlapping.
The output of the UNet is a heatmap (...
- 111
1
vote
0
answers
24
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 ...
- 175
1
vote
0
answers
76
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 ...
- 493
1
vote
0
answers
150
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 ...
- 61
0
votes
2
answers
989
views
Using pre-trained models on image dataset that is totally different for object detection?
I have been trying out various tutorials on object detection machine learning. All the tutorials so far have been to use a pre-trained model for practical reasons when detecting objects that the pre-...
- 103
0
votes
1
answer
239
views
Image segmentation with varying resolution
I am looking to create a model that is able to perform binary segmentation of images with varying resolutions. For model should be able to classify tree or not tree regardless of the resolution of the ...
- 101
0
votes
1
answer
130
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 ...
- 263
0
votes
1
answer
76
views
How to add engineered features to an image segmentation model
I have built a U-net model for image segmentation of 3-channel remote sensing images. I have a total of four classes; two of these classes look very similar and are hard to distinguish in the images ...
- 1
0
votes
1
answer
58
views
How to divide a segmented image into classes instances?
Is there a method/algorithm to generate instances of objects from image that was segmented by the use of any image segmentation models?
For example, I have an image with one class and it was segmented ...
- 1,280
0
votes
1
answer
266
views
Semantic segmentation failing in small instance detection
I performed semantic segmentation with U-net. My dataset consists of grayscale images of defects. After training the dataset for I got an metric accuracy of only 0.3 - 0.4 IOU. Eventhough it is merely ...
-1
votes
1
answer
641
views
What is exactly sparse annotation?
What is exactly sparse annotation? Is it different from labeling images?
I've been reading a paper about vessel segmentation and have some issues understanding this part.
-1
votes
2
answers
315
views
Semantic segmentation CNN outputs all zeroes
I'm using MATLAB 2019, Linux, and UNet (a CNN specifically designed for semantic segmentation). I'm training the network to classify all pixels in an image as either cell or background to get ...
-1
votes
0
answers
20
views
How to change a single object detection network to a multiple object detection network?
I have trained a CNN network to detect a circle and approximate its centre and radius in an image. What I want to do now is detect the centre and radius of all the circles if there are multiple ...
- 131