All Questions
Tagged with image-segmentation deep-learning
29 questions
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16
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How to 'induce' or 'teach' pretrained model to a continous Transformer token-pruning Algorithm
I am currently looking for ways to improve Transformers performance in image processing, especially in image segmentation. I found this paper by Kong, Z., et al called "SPViT: Enabling Faster ...
- 1
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41
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Realtime cuboid vs cylinder classification of a 2D mask / object from a 3D scene?
Most realtime SOTA segmentation/detection model can reliably segment an object from a 2D input, and I can get the contours/polylines describing its edges in realtime. By realtime, I'll consider ...
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54
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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 ...
- 125
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318
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Use AI/Computer Vision to detect scene changes
I'm trying to use AI and computer vision techniques to identify scene changes for a camera. Something like this:
What are some approaches to do this? Any ideas?
The scene is static. Somewhere I saw a ...
- 983
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1
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37
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Should I apply a min-max scale (range 0 to 1) before applying the normalisation or should I apply the z-score normalisation directly?
I want to implement a neural network in Pytorch for medical image segmentation. I should normalise my data.
Should I apply a min-max scale (range 0 to 1) before applying the normalisation or should I ...
- 101
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57
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Creating border around specific areas of images
I have some 1000+ image, containing data like this
Red area: Symbols
Grey area: Text describing the symbol
Note: I draw these red/grey boxes just for visualization only.
Each symbol is unique in this ...
- 111
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1
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4k
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What's the difference between classification and segmentation in deep learning?
What's the difference between classification and segmentation in deep learning?
In particular, can the classification loss function be used for segmentation problems?
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1
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109
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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 ...
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1
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133
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Is batch size of 1 a valid choice for a very deep neural network with high memory requirement?
I am training a very deep neural network (Panoptic-DeepLab) with a ResNet34 backbone on Google Colab on CityScapes dataset for Panoptic Segmentation, and noticed that, with a big crop size, the batch ...
- 111
-1
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1
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206
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Use of Mask in U Net for plant disease detection [closed]
I am using U-Net for plant disease detection. I am new to deep learning and computer vision.
Currently, we are feeding the masking images generated via open cv HSV format to detect colours from the ...
-1
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1
answer
641
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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.
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313
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Mask R-CNN: how is the inference done?
According to the Mask R-CNN paper and the picture below (taken from the paper), the mask branch is computed in parallel with the bbox classification and regression branches.
However in the paper they ...
- 21
1
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3
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673
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Aside from dice score, what other good metrics are used to evaluate segmentation models?
I have a segmentation which outputs only one channel image (2 class segmentation). I have used dice score for most of the time, but now higher powers in my team want me to expand evaluation metrics ...
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19
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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 ...
- 133
2
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20
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Predicting the the motion of a 3D object when the motion of a set of markers is known
trying to figure out where to get started with this:
I have a few hundred CT images where certain three-dimensional features in the image (anatomy) are moving in a correlated fashion with a set of ...
- 21
4
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2
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4k
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Unet Overfitting for binary segmentation of fake images
I am working on a project where I am trying to detect and localize forgeries in images. I am using the CASIA v2 dataset and using Unet model for the task. I have the binary masks of all the images in ...
1
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1
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168
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How to use mixed data for image segmentation?
I have a task for which I have to do image segmentation (cancer detection on MRIs). If possible, I would also like to include clinical data (i.e. numeric/categorical data which comes in the form of a ...
- 115
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203
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What does Dice Loss should receive in case of binary segmentation
I implemented Dice loss class in pytorch:
...
- 188
1
vote
1
answer
386
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Training a classifier on different datasets with different image conditions for different labels causes the model to infer using the background
I have an interesting problem related to training the model on two different datasets for the target feature on images taken on different conditions, which might affect the model's ability to ...
0
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1
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266
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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 ...
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150
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Is Webpage Semantic Segmentation possible nowadays?
I'm trying to do some research about semantic segmentation for webpages, in particular e-commerce webpages. I found some articles which provide some solutions based on very old dataset and those ...
- 199
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1
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91
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How do we make our outputs to have the same size as the true mask?
When we are doing multi-label segmentation tasks, our y_true (the mask) will be (w, h, 3), but, in our model, at the last layer, ...
- 57
1
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467
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Is it necessary to label the background when generating the labelled dataset for semantic segmentation?
When I label images for semantic segmentation (using u-net, if that matters), is labeling the background (anything I am not interested in) necessary? Will it improve the network's performance?
- 111
1
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1k
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How to compare SegNet, U-Net and EfficientNet?
SegNet and U-Net are created for segmentation problem and EfficientNet is created for classification problem. I have a task and it is saying that train these models on the same dataset and compare ...
- 121
2
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30
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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 ...
- 1,369
2
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298
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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
3
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152
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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 ...
- 131
3
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1
answer
333
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“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 ...
- 271
1
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38
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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 ...
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