Questions tagged [image-processing]
For questions related to image processing (in the context of AI).
136
questions
2
votes
1answer
30 views
What is the stride information of an image referring here?
In convolutional neural networks, the convolution and pooling operations have a parameter known as stride, which decides the jump the kernel needs to do on the input image. You can get more ...
0
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0answers
23 views
Custom LRscheduler and val loss logging in detectron2 [closed]
I want to add validation loss logging in the training process of detectron2 MRCNN.
I also want to add a LR scheduler in the process as the inbuilt one is multiplier.
I have configured the code for ...
1
vote
1answer
25 views
What is meant by sub-region of an image?
Consider the following sentences from the research paper titled PatternNet: Visual Pattern Mining with Deep Neural Network by Hongzhi Li et al.
The value of each pixel in a feature map is the ...
0
votes
1answer
14 views
Simple Image-based example for not utilising the variable-sized input handling capability of a Convolutional neural network
Convolutional neural networks are capable of handling inputs of varying sizes. It is one of the key benefits of convolutional neural networks. But I am unsure about the cases when we should not ...
1
vote
0answers
28 views
Is there any way to remove background of an image fully with the help of post-processor techniques(like edge detector) after deep learning based model
I'm using a deep learning-based model (deep lab v3+ with xception as the backbone) for image segmentation and removing the background. The subject of the image will be a person. And my target is to ...
2
votes
1answer
45 views
What is the name of the method for the smart extend of image surroundings?
I'm looking for the name of the method (or algorithms family, or research body) used for the smart extend of image surroundings.
For example, the method I'm looking for would take this image:
And ...
0
votes
0answers
33 views
variational autoencoder - decoder output for images
Following the standard setup/notation for a VAE, let $z$ denote the latent variables, $q$ as the encoder, $p$ as the decoder, and $x$ as the label. Let the objective be to maximize the ELBO, where a ...
9
votes
3answers
747 views
Is it okay to use publicly available Instagram videos to train an AI?
Since I haven't found any good training data for my university project, I want to use pictures and videos from public Instagram profiles. Am I allowed to do that?
0
votes
0answers
31 views
Why do some of the algorithms take some extra space around the actual bounding box?
In some of the algorithms, there is a need to crop the object in an image. So, bounding boxes need to be used in order to crop the image to contain object only. Bounding boxes provide the information ...
0
votes
1answer
27 views
How to understand the common practices followed for writing a "bounding box" for an image in datasets?
For the image datasets, there may be a bounding box for each image at the dataset. It is an annotation for an image. It is a rectangular box intended for focusing on something inside the image.
I read ...
0
votes
0answers
29 views
Uniform representation of images for machine learning
I'm new to the field of ML so please bear with me while I try to explain what I'm looking for. In most machine learning pipelines that deal with images there is a requirement to "normalize" ...
0
votes
0answers
19 views
How to ensemble two different computer vision models?
I have prepared two distinct models:
Representing contour of the image
Representing edges of the image.
I would like to create a model which can take advantage of both models in predicting data. May ...
0
votes
0answers
15 views
Preprocessing images for test and validation datasets for training a convolutional neural network (CLAHE)?
I'm training a convolutional neural network for image classification,and i want to preprocess the images, for example with the CLAHE method. I'm not sure if this preprocessing has to be used on the ...
1
vote
1answer
48 views
Why do some techniques use random augmentations during convolution processes
While going over PyTorch image augmentations, https://pytorch.org/vision/stable/transforms.html, I see that some augmentations can be applied with a certain probability. What is the purpose of ...
0
votes
0answers
16 views
What is the significance behind having small kernel sizes over having one large kernel size that covers the entire input in a CNN?
I have hardly ever seen anyone cover the entire input image with a filter of the same dimensions. I was wondering why that is the case, and if the performance in say, an image detection application ...
0
votes
1answer
23 views
Material(s) for understanding "image channels"
I am pretty confused about the concept of "image channels".
I want material that explains the concept of channels from scratch to whatever is required to understand their role in machine ...
2
votes
1answer
192 views
What do equations 1 and 3 describe in the "Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels" paper?
This paper uses image augmentation to improve RL algorithms. It contains the following paragraph -
"Our approach, DrQ, is the union of the three separate regularization mechanisms introduced ...
-1
votes
1answer
30 views
how produce image of face working with AI [closed]
I came across a https://generated.photos/ site that claims to produce images entirely by artificial intelligence.
My question is how does this program work? What mechanism and libraries should I use ...
1
vote
1answer
44 views
What does 'input planes' mean in the phrase 'input signal/image composed of several input planes'?
PyTorch documentation provided the following descriptions to the Convolution layers
...
2
votes
1answer
78 views
What does 'channel' mean in the case of an 1D convolution?
While reading about 1D-convolution in PyTorch, I encountered the concept of channels
...
1
vote
0answers
12 views
How to approach receipt interpretation with neural networks
I have never worked with neural networks before, but I want to learn and I have a specific use case that I would want to solve (or at least try to).
I have developed software for multiple years, in a ...
0
votes
0answers
20 views
What image augmentations can help a neural network identify the smallest pixels within an image?
I am training a CNN to identify objects and I believe the network will learn much faster if it can learn to focus on the smallest pixels. One way to go about this would be to augment the images before ...
0
votes
1answer
37 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.
<...
1
vote
3answers
178 views
Why is AI Super Resolution Reconstruction more than just guessing?
I saw a video on Youtube about AI and Super Resolution Image Reconstruction with TecoGAN. I must say I am impressed.
Now, I am wondering how reliable this is.
I have learned at university that you ...
2
votes
0answers
27 views
Convolutional Neural Network (CNN) with Tree architecture to organize the number of classes
At the moment, I have around 1.000 classes with accuracy and loss that are acceptable. In the long term, there could be more than 100.000 classes. The main problem is that every time a new class is ...
2
votes
0answers
29 views
Understanding SIFT descriptor calculation
I need to understand how SIFT calculates the descriptors for the keypoints.
Intuitively, i understand that it takes each keypoint, calculates the gradients for each pixel in a neighborhood of the ...
1
vote
0answers
51 views
What do "spatial" and "temporal" mean in the context of image processing?
I am new to image processing. I am trying to understand CNNs from this blog post. Here's an excerpt from that article that mentions these terms.
A ConvNet is able to successfully capture the Spatial ...
0
votes
0answers
45 views
Bounding box transformation using point cloud
I am working on a project in which I have an RGB Image and the corresponding 2d bounding boxes for the objects in the image. I also have a respective point cloud and therefore, I can extract the depth ...
0
votes
1answer
244 views
Feeding CNN FFT of an image, a dumb idea?
My dataset consists of about 40,000 200x200px grayscale images of centered blobs bathed in noise and occasional artifacts like stripes other blobs of different shapes and sizes, fuzzy speckles and so ...
0
votes
0answers
25 views
What is "fill" algorithm used for image resizing and cropping?
I was going through this documentation directed by Codelab-Developer-Google. In order to resize an image, the notebook is using the "fill" algorithm. See the below code
...
0
votes
0answers
17 views
New image-to-image translation algorithm for other type of tasks
I found this amazing new research paper "High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network" and an associated video.
It's about a new ...
2
votes
1answer
72 views
In style transfer, why does the comparison between channels give a good sense of style?
I have been learning about Style Transfer recently. Style is defined as
The correlation of activations between channels.
I can't seem to understand why that would be true. Intuitively, style seems ...
2
votes
0answers
17 views
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 ...
2
votes
1answer
35 views
Should one rescale (normalize) image before or after data augmentation?
During image preprocessing pipeline, should one rescale each pixel value to [0, 1] by dividing 255 first, and then perform data transformation such as color distortion, gaussian blur? or vice versa?
I ...
0
votes
0answers
36 views
Why is the F-beta score not increasing while the validation loss fluctuates?
I'm trying to implement a multi-label image classification from a CT scan data set. The goal of the work is to find out which CT scan image has eleven of the most common fractures if it is fractured. ...
2
votes
1answer
47 views
Viola-Jones algorithm: Haar-like features, how are the features extracted?
If I have an image like this
1 2 3 4 5 6 7 8
a b c d e f g h
...
And I apply a Haar-like feature with a template
...
0
votes
0answers
33 views
Autoencoder on Sharp Images
I am training an autoencoder to reconstruct 3D images. This is going quite well apart from one slight issue.
The images I wish to reconstruct are binary representations of organs. This means that they ...
1
vote
0answers
38 views
SAGAN - is there a mistake in the original paper?
in the original paper the following scheme of the self-attention appears:
https://arxiv.org/pdf/1805.08318.pdf
In a later overview:
https://arxiv.org/pdf/1906.01529.pdf
this scheme appears:
...
1
vote
0answers
29 views
For image preprocessing, is it better to use normalization or standartization?
For a neural network model that classifies images, is it better to use normalization (dividing by 255.0) or using standardization (subtract mean and divide by STD)?
When I started learning ...
0
votes
1answer
59 views
What amount of ressources is involved in building an image recognition system?
I would like to have an order of magnitude of ressources required to build an image recognition system.
Let say you want to build a startup company which main product will have to distinguish 20 ...
0
votes
0answers
14 views
How can I improve the robustness of my Fire Detection algorithm in openCV?
I am working on a project to detect fire in CCTV or any other surveillance cameras. Up till now I have completed the following stages;
Convert the RGB into HSV
Sliced out the Value matrix from HSV
...
0
votes
0answers
18 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 ...
2
votes
1answer
122 views
Is it a good idea to use different width and height of the kernel in a CNN?
I always see that the width and height of the kernel are the same. But is it a good idea to use different numbers?
Recently I tried to use GoogLeNet (which expects images to be 224x224) on my images (...
3
votes
0answers
39 views
Best Machine Learning Model for "Predicted" Image Generation
I am currently working on undergraduate research to determine hotspots for hand-surface contact. Ideally, I would like to give the model a depth image as input:
Example of synthetic depth image
and ...
1
vote
0answers
42 views
Does the order of data augmentation and normalization matter?
What is the preferred order of data augmentation and normalization? Is it the former followed by the latter?
0
votes
1answer
46 views
Denoising Images When Training a Classification Model
Suppose you have a binary outcome variable and have some training data (10,000 images in jpg format). Also you have a test set of say 11,000 images. If we want to train a classification model and want ...
3
votes
0answers
50 views
Is the GAN architecture better suited for medical image denoising than the CNN?
I'm considering using GANs for medical image denoising, based on previous literature, like this and this. My input to the GAN would be a high-noise image and my ideal output would be a low-noise, high-...
0
votes
0answers
52 views
Can I use a CNN for template matching, so that there is robustness, as the background of the target image is not that good?
I have to extract part of a source image, then I have to check if it is similar or almost similar to any of the 10 target images, so that I can do further processing on that one specific target image, ...
0
votes
0answers
28 views
AI generator for imaginary street maps?
Similar to This person does not exist or This artwork does not exist, how might I go about creating a This street map does not exist, including choosing an appropriate AI model and scoping features?
...
2
votes
1answer
71 views
What algorithm would you advise me to use for my task?
I have an image and a mask. I want the image to be the same, but rotated, scaled and positioned like mask. What can I use?
