Questions tagged [image-recognition]

For questions related to image recognition in the context of AI.

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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 ...
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27 views

Yolo from scratch dataset and output

Hi I coded a YOLO model from scratch and just came to realise that my dataset does not fit the models output. This is what I mean: The model outputs a ...
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1answer
58 views

Predicting continous value with CNN (prediction of fruit maturity)

I want to train some IA algorithm to be able to evaluate the maturity of a fruit (say, measured in numbers of days before rotten) based on an image of the fruit. My first instinct is to go with ...
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What's the best machine learning algorithm / neural network architecture to use for a task that maps between images and textual descriptions of them?

Title says it all really. I want to train a network to take images of diagrams and produce a standard textual definition of them. What ML architecture is best for this?
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How is few-shot learning different from transfer learning?

To my understanding, transfer learning helps to incorporate data from other related datasets and achieve the task with less labelled data (maybe in 100s of images per category). Few-shot learning ...
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1answer
45 views

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 ...
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Considerations when doing image classification where the object is not the subject

I've come across two types of image classification tasks cat/dog classification the whole picture is either a cat or a dog. Simple. this image contains a cat classification. There's a whole chaotic ...
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23 views

How to build a commercial Image-Image search engine using LSH / Near Duplicate or some other algo on more than 20M images

TL;DR: HOW DO I APPLY LSH WITH A DEEP LEARNING MODEL TO BUILD A IMAGE-IMAGE SEARCH ENGINE ON >20M IMAGES? I want to build a system where I am helping my ...
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62 views

Can a convolutional neural network classify text document images?

I know convolutional neural networks are commonly used for image recognition, but I was wondering if they would be able to distinguish between predominantly text-based documents vs something like ...
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28 views

Is it possible to use self-supervised learning on different images for the pretext and downstream tasks?

I have just come across the idea of self-supervised learning. It seems that it is possible to get higher accuracies on downstream tasks when the network is trained on pretext tasks. Suppose that I ...
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23 views

Training a model to identify certain differences between images?

Newbie to CV here so sorry of this is basic. Here's the deal, I have a program that I run many times. and each run I produce a screenshot. I need to compare screenshots from N-1 and N runs and make ...
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Estimating depth/perspective of image

I'd like to find a method in which the depth or perspective of an image is estimated. I imagine this could perhaps be done based on how quickly classified objects, such as cars or humans, grow or ...
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Face detection and replacement in photos

I have 2 photos, and my goal is to detect the face in one and place it on the face of the person in the other photo- basically face detection and replacement. It's not deep fakes. It's more of a ...
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How does one measure image similarity using Radial Basis Kernel?

Here is the formula of a radial basis kernel $$ k\left(x_{i}, x_{j}\right)=\exp \left(-\frac{d\left(x_{i}, x_{j}\right)^{2}}{2 l^{2}}\right), $$ where $x'$ and $x$ are feature vectors. I have two very ...
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What are ways to learn a classifier for labelling a series of images rather than individual images?

... and how do I reword my question in the title? I have a dataset where each "instance" has a "series" of multiple photos taken from different angles. I need to classify each ...
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CNN to detect presence/absense of label on images with mixed labels

Here's my problem: I work with medical image classification, and currently I have 3 classes: class A: images with lesion 1 only; and images with lesion 1 and N other lesions class B: images with 2 ...
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1answer
40 views

Are there any known models/techniques to determine whether a person in a store is a customer or a store representative?

Are there any known models/techniques to determine whether a person in a store is a customer or a store representative? For example, customer representatives can wear uniforms and then one possible ...
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1answer
50 views

How can I train a CNN to detect when a person is smoking outside of shop given images from a video camera?

My friend is working at a pizza shop. He takes cigarette breaks in an area that is covered by the public webcam of our town. I now want to train a convolutional neural network to be able to detect ...
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22 views

Machine Learning Techniques for Objects Location/Orientation in Images

what Machine Learning tool can understand in which location and orientation a picture was taken from? That is from pictures of similar objects, say for example pictures of car interiors. So given a ...
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1answer
27 views

Image Classification for watermarks with poor results

Just starting learning things about tensorflow and NN. As an exercise I decided to create a dataset of images, watermarked and not, in order to binary classify these. First of all, the dataset ( you ...
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37 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 ...
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Would it be possible to use AI to measure pupil dilation diameters and fluctuation, on video films on a regular webcam?

I've been researching the topic of Cognitive Load Measurement through pupil dilation measurement. All solutions to pupil dilation measurement require some kind of special hardware setup. I was ...
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1answer
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Should I remove the text overlaying some images in the dataset before training the CNN?

If I am attempting to train a CNN on some image data to perform image classification, but some of the images have pieces of text overlaying them (for the purpose of description to humans), then is it ...
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144 views

Is continuous learning possible with a deep convolutional neural network, without changing its topology?

In general, is continuous learning possible with a deep convolutional neural network, without changing its topology? In my case, I want to use a convolutional neural network as a classifier of ...
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Can we identify only the objects in specific parts of an image with computer vision?

I am studying computer vision for the past 3 months. I have come across the object identification problem, where given an image, CV would identify various parts in the image. If I give an image, and a ...
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41 views

How to normalise image input to backpropogation algorithm?

I am implementing a simple backpropagation neural network for classifying images. One set of images are cars another set of images are buildings (houses). So far I have used Sobel Edge detector after ...
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Why isn't medical imaging improving faster with AI?

Researcher here. I just read this piece about medical imaging ai with object recognition and it left me wondering why there are still 100,000+ deaths a year in the US due to misdiagnosis - anyone out ...
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35 views

Why is the convolution layer called Conv2D?

When I build a convolution layer for image processing, the filter parameters should have 3 dimensions, (filter_length, filter_width, color_depth) is that correct? ...
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11 views

Detect and overlay a black TV on a video

I have a short video where a TV is shown. I need to detect the TV there (let's assume it's all pure black or it's covered with a green screen), and overlay a video on top of it on the same area. I ...
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28 views

How should I label images to get high accuracy with YOLO?

I am new to Object Detection with Yolo and I have questions regarding the labeling (for custom objects): Is there any guideline or tips on how to label images to have high accuracy at the end? ...
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30 views

Image classification on SVG format

To best of my knowledge, images are usually fed in pixel format to ML models. Is there any work that does image classification where the image format is SVG?
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The convolutional network architectures with enhanced invariance

It is well known, that CNN have advantage with respect to the Dense neural networks in the image classification and other pattern recognition tasks, because they have a translationall invariance built ...
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Is it a good idea to train a neural network to classify images without base-hypothesis?

I'm a relative beginner in deep-learning (understand by that, I'm doing my first kaggle competition right now, and I have loads to learn still) and I was just wondering something. Let's say you have ...
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Which neural network should I use to distinguish between different types of defects?

I want to teach a neural network to distinguish between different types of defects. For that, I generated images of fake-defects. The images of the fake-defect types are attached. I tried many ...
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What could be the possible strategy and Deep Learning method that MathPix might be using for LaTex detection?

I want to build an open Source OCR just like MathPix. There is already a model to extract LaTex from the image by Harverd NLP's im2markup but the problem is that their data has been trained and tested ...
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31 views

Is there a developed model for image classification of photo or not photo?

I'm curious if there is current research or a common classification model for determining whether an image is a photo (as in taken with a camera) or something else (such as a vector, screenshot, or ...
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1answer
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Detect data in tables of roughly the same structure

I would like to train a model that serializes a table of nutrition facts into it's values. The tables can vary in form and colour, but always contain the same set of keys (e.g. carbs, fats). Examples ...
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Approaches for OCR building which can extract latex from the image as mathematical formulas

I have images of questions from the domain of mathematics, where the image can be a mixture of the English language and mathematical formulas. I want to build and train an OCR model like Harvard NLP's ...
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2answers
114 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 ...
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50 views

How to prevent image recognition of my dataset with neural networks and make it hard to train them?

Suppose I have a private set of images containing some objects. How do i Make it very hard for the neural networks such as ImageNet to recognize these objects, while allowing humans to do it at the ...
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Binary classification to recognize blobs on pictures generates many false-positive results

I am training a NN for blobs vs non-blobs recognition. Blobs example: Non-blobs: Keras architecture is: ...
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Which model structure is best suited to build a Math OCR (img2latex)? RAM, DRAM, CRNN or Attention OCR?

I am trying to build an OCR which can read the Mathematical equations just like MAthPix and im2markup. im2markup by HarvardNLP seems like a good model but the thing is that it is built using Torch and ...
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15 views

Can attention with 2d position encoding beat capsule on cv tasks?

I have always had doubts about the necessity and intuitive/theoretical justification for capsule network in image classification and more recently nlp tasks. For the former, in order to address the ...
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1answer
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Why should the baseline's prediction be near zero, according to the Integrated Gradients paper?

I am trying to understand Intagrated Gradients, but have difficulty in understanding the authors' claim (in section 3, page 3): For most deep networks, it is possible to choose a baseline such that ...
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37 views

Which tool can I use to detect “visual defects” on a photo of a product?

I am looking for a tool that could detect visual defects on a photo of a free flowing product like potato flakes. Potato flakes is powder-like product that is essentially dedydrated mashed potatoes. ...
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49 views

How to detect forgery on scanned document images?

I am trying to detect forgeries done after a document is scanned by a scanner. I already tried to access the metadata, and, if it is edited with any software after scanning, then it is easily detected ...
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Does anyone know of a model for comparing the eyes of people in two images to see if they match?

There’s a lot of talk of undercover cops intentionally starting violence in otherwise peaceful protests. The evidence, primarily, are images like this. https://images.app.goo.gl/4n3o2EXwFzMQfsKq6 ...
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Detect object in video and augment another video on top of it

I'm trying to detect an object in a video (with slight camera movement), and then augment another video on top of it. What is the simplest approach to do that? For instance, let's assume I have this ...
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18 views

How can I efficiently detect subsections?

I have a feeling this question has a lot of research into it, but I can't find any relevant results. I'm trying to compare the similarity of audio Here, I have 2 virtually identical samples; however,...
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42 views

Is there an AI tool to reverse engineer scanned data to obtain its CAD file?

Today, if you scan an object and want its CAD file (Solidworks/Autocad), you need to use reverse engineering software (Geomagic). This takes time and you need experience of the software tools. Is ...

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