Questions tagged [image-recognition]
For questions related to image recognition in the context of AI.
298
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How to accurately detect grid cell boundaries in Python image processing?
I'm working on a Python algorithm to detect individual cells of a grid passed by an image. Currently, I'm facing an issue where the values inside each cell are being selected as contours along with ...
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How to create meaningful features that allow unsupervised image classification?
I would train features that can later be correlated with categories, once I have some examples for the categories. Let's say one has a set of training images sorted by artist, and wants to create some ...
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22
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What are general techniques of structuring an image classification Neural Network for very large numbers of output classes?
I am aware of Neural Networks that have 100K+ classes and I would like to build one myself (yes, I have lots of training data) but I am unsure which technique to use because most of the nets I have ...
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9
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Training ImageNet on Resnet - Dropping LR has little improvement on accuracy
I'm trying to train Resnet50 on Imagenet following this paper [1] as well as this one[2].
They say that at approximately every 30 epochs, I should drop the learning rate by 10.
Since I'm training on 8 ...
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How do I balance context and history when creating prompts for LLM's?
A conversation through the OpenAI API looks something like this
...
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42
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How to do image classification with optional metadata?
I have a vanilla image classification problem. The image may optionally have some numerical metadata associated with it. We don't assume uniform availability of this metadata, i.e., the model should ...
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13
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What are some good pairs of transfer learning source and target datasets for image classification?
As the title says, I'm curious about some well used transfer learning tasks.
ImageNet to other datasets is common, but what are something good pairs I can try and mess around with ?
Like CIFAR10 to ...
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What is the best lightweight alternative to VGG16 for image fingerprinting?
I am using a VGG16 model with the classification layer stripped off to generate vectors for an intermediate stage of an image fingerprinting algorithm. It works well, but VGG16 is a little hefty, and ...
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High Accuracy ML.NET Image differentiation model
I have a relatively big dataset (100+GB) that has 35 categories. All of them are microscopic images with slight differences. Although ML.NET documentation itself declares that training time should be ...
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Challenges in Developing AI Algorithms for X-ray Image Analysis on Large Datasets
Hello everyone,
I'm currently working on a research project involving X-ray imaging
and the development of AI algorithms to detect diseases from large
...
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How can CAPTCHAs be used for both user verification and ML training?
CAPTCHAs (e.g. requiring a site visitor to click all the images of traffic lights in a grid of images) are often used throughout to Internet to verify that a site visitor is a human rather than a bot.
...
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Empty space detection [closed]
I'm looking for a TensorFlow model detecting empty spaces on the images. I need to add my company logo to this empty area so there shouldn't be any faces or objects in this area.
Also, I would be ...
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Handling Feature Selection Discrepancy in Image Classification Model
I have developed an image classification model that categorizes images into two classes (we'll say good and bad for the sake of example) based on a set of tags. To improve the model's performance, I ...
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43
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Can a neural network recognize cropped images?
I asked ChatGPT to list some algorithms for identifying if one image is a cropped version of another or not. It suggested four algorithms that I know won't work, plus one that amounted to "train ...
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147
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Tips for solving OpenAI/Faramas Gymnasium Car Racing Environment
Im quite new to ML and wanna solve Gyms Car Racing v2 using Q-Learning with a Q-Table.
But I am having problems approaching this. Thats why I am hoping someone more advanced in this field could give ...
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What is the best approach to remove this additional container from the cropped image?
I'm working on a computer vision application in Python to analyze images of ice cream cuttings to measure the amount of variegate(ie. fruit syrup or fudge) compared to the base ice cream. My approach ...
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Are image classification nets independent of input size ? Which ones?
Most models I have seen have a dense layer at the exit of the network with a softmax function or a relu sometimes, so I thought this was confusing:
The major hurdle for going from image ...
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181
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Should I use pretrained model for image classification or not?
I have thousands of images similar to this.
I can classify them using existing metadata to different folders according to gravel product type loaded on the truck.
What would be optimal way to train a ...
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Is it feasible to perform facial recognition on hundreds of thousands of individuals?
I came across a video with the title "you can buy things with your face in China". in the video, a woman scanned her face into a vending machine to buy a drink with only her face and without ...
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757
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Is the GPT-4 for text the same model that can input and output images?
Currently, the published GPT-4 can input and output text.
A version of GPT-4 that can input and output text and images exists, according to the technical report, but is not yet publicly available.
I ...
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180
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Out-of-domain generalization
Given $X$ the space of all $N \times N$-pixel images and $I=\{$airplane,clock,axe,...$\}$ a set of labels.
An image classification task is generally concerned to learn a map
$$F:X \rightarrow I$$
Let'...
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493
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How to detect outlier images?
Before I describe my challenge, I want to point out that I have searched extensively online for "outlier image detection", "anomaly images detection", etc., but all returned ...
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44
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Higher accuracy in the test set than in the training set
Hi I'm trying to train an ANN model to classify images containing these characters: 0,1,2,3,4,T,X,S
eg.
etc...
so something like the classification of records of the MNIST dataset but using my ...
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18
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How does FaceNet (or similar) bootstrap new faces?
In a metric learning system the system can be trained on known examples such that common classes (faces) are clustered together and separated from each other as much as possible. If triplet loss is ...
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74
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Graph recognition with machine learning?
Let's say we have drawing of graphs (in the graph theory sense).
Is it possible to use machine learning to convert such drawing into a format that is understandable by computers, such as a list of ...
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61
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Best methods to square rectangular images for OR
I've read previous posts that assert using one of these solutions:
crop and or resize
nn input size independent
In my case, I am using some tensorflow models and afaik they report a fixed size like ...
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36
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How to deal with varying number of input images?
Im trying to use Deep-Learning to recognize breast cancer on Mammography Images. But in the dataset every patient has a different (1-4) number of images taken. How can i deal with that? Generally i ...
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146
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Should a CNN generalize to arbitrary positions in the data?
I have trained a CNN on one dimensional data that is the power spectral density (PSD) of a $N$ different classes of signals ($N=4$). Each of the $N$ signals has a different spectral shape (not shown ...
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72
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Why didn't my convolutional image classifier network learn anything?
So I am trying to make a CNN image classifier that has two classes, good and bad. The aim is to look at photoshoot pictures that can be found on fashion sites and find the "best one". I ...
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102
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How can I use CNN to make a cumulative count of the number of occurrences of each of the different objects in all the images in the test set?
Let's say there are three images in the test set, the first with three triangles, the second with two triangles and two circles, the third with four circles and two squares, and the final tally is a ...
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How to model a few shot image classification task similar to a traditional supervised one?
I want to train an image classification model. I have 10 classes with 15 images per class. Since the data is very less, I thought of modeling the problem as a few-shot image classification task and ...
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121
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Image classification problem with multiple right classes
I have a use case where the model needs to detect fabricdefects. There are 15+ different kinds of defects. In one image there can be multiple defects present. The straight forward solution for this ...
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88
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Are there metrics for image complexity for informing neural network design?
BACKGROUND: I am trying to think of rational approaches to designing deep learning models for image classification. One thought is to quantify the complexity of image datasets and use that to inform ...
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203
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Is there an image classification dataset where the class depends on spatial relations?
My question is pretty much the one asked above. To clarify a bit further: I have only found datasets that do object localization and that also have relations between the objects annotated (like: "...
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What kind of neural network and GPU should I use to classify images into > 10 000 classes?
I am trying to developp an image classifier that would have more than 10 000 classes but I don't know what kind of neural network I should use ?
Some Other questions arise from this one :
How big ...
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230
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Examples where AI fails in revealing ways
For a short presentation about AI I am looking for examples where AI failed and therby shows the limits of itself.
I remember there was one examples, where an image classifier was given an image of ...
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Mapping an image to a well defined object using OpenCV
I am completely new to computer vision and I am working on a small hobby project.
The goal is to use camera footage of a foosball table to map the image to already well defined object geometry with ...
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Why does my neural network perform different on the same images during training and testing?
I use tensorflow keras to build a neural network that classifies images of covid-19 rapid tests into three classes (Negative, Positive, Empty).
During training the ...
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60
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At what size does a picture become unusable for facial recognition?
Lets say i have a portrait photo of which the face it contains covers about 90% of the entire photo. I want to be able to detect the face in this photo using facial recognition but i also want to ...
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ImageNet Dataset (for PyTorch VGG16 training)
Please can someone describe how to properly obtain the ImageNet dataset (to be precise the ImageNet 2012 Classification Dataset).
What I attempted so far
The ImageNet webpage refers the user to ...
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Can an AI generated image (such as pic of human face) be detected that it's AI generated?
AIs are getting better and better at creating images and art. Some of the stuff is almost impossible to be detected by the naked eye. But what about programs and algorithms? Instead of creating an ...
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140
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How can I reduce the loss? Why do I have the high loss and why do I have the gradient?
I want to classify some images (there are about 200.000 images) with a CNN. But I get a very high loss, see figures:
Loss over the hole training run
Loss for each epoch
It's confused me, that there ...
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693
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For an image (of any object), how to find its location in the other image(s) which contains it, given there are no labels or annotations for any image
Problem Statement:
I am given 2 sets of images. All the images in both sets are without annotations and labels.
First set : a set of images of the grocery store shelves (captured in the grocery stores)...
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289
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How do I deal with a dataset of Images with variable sizes (width and height) when doing Image Classification?
I have a dataset in which the images which don't have the same width and height. How do I perform Image Classification with such images? I am trying as much as possible to steer away from image ...
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49
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Image Recognition Method, calculate deviation from rectangular grid
I have a set-up which creates pictures of a grid that is a bit bend towards the ends, and I need some kind of program that can calculate the deviation, resp. it just needs to be some kind of indicator,...
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66
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How to convert prediction probabilities of 2D images (initially 3D image) to 3D image predictions?
Classification: binary
Model: CNN (ResNet50V2)
During our research we've had 91x109x91 images (3-dimensional). We've used 2D CNN to train and evaluate our images and make predictions on labelled cases,...
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69
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Does Using the Same Background for Binary Classification Improve Model Accuracy?
I am training a CNN that detects if a there is a pot of boiling water vs if there is a pot of boiling water with pasta inside. My hypothesis is that having the same background for both a positive and ...
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Is AI able to detect major changes in pairs of images while ignoring minor changes (due to tree crown growth, color and perspectiv disstortions)?
I'm starting to get involved into machine learning but still have some troubles to select the approriate tool or algorithm.
My basic task is to compare remotly sensed images of individual trees at two ...
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813
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Musical notes interpretation [closed]
Musical notes
Musical notes videos
Piano
Can AI, Machine learning, Data science, Computer vision, image processing technologies assist in interpreting musical notes ?
Input dataset : Musical notes
...
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Detecting cheats visually using AI
I really like to play my favorite 3D shooter game online. Unfortunately, it is really old and cheat protection isn't really common there, but cheaters are! It is very frustrating, because it really ...
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