Questions tagged [image-recognition]

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

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16 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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What is 3D face recognition? and how we can check liveness of a face image?

Actually what is mean by 3D face recognition? In normal cases we are extracting face encoding s from a 2D image,right? Is 3D face recognition is used for liveness detection? how its possible?
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How can I use autoencoders to analyze patterns and classify them?

I generated a bunch of simulation data from a complex physical simulation that spits out patterns. I am trying to apply unsupervised learning to analyze the patterns and ideally classify them into ...
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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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101 views

Why is this ResNet50 misclassifying objects?

I'm new to Deep Learning, and I have some conceptual problems. I followed a simple tutorial here, and trained a model in Keras to do image classification on 10 classes of logos. I prepared 10 classes ...
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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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Automated Annotation of Objects

Given thousands of images, where some of the images contain target objects and others do not, is there an easy way of drawing bounding boxes on these target objects rather than relying on manual ...
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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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1answer
21 views

Using convnet to classify language of text contained in images

I hope this question is not too broad or general. I have a very large set of images all of which contain text (some have more, some less). All of them have been tagged as containing, say, English text ...
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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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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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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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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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1answer
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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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1answer
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What is the difference between exhaustive nearest neighbor search and k-nearest neighbour search?

I have two lists of feature vectors calculated from pre-trained CNN for image retrieval task: Query: FV_Q and Reference FV_R. <...
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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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How successfully can convnets detect NSFW images?

For example, search engine companies want to classify their image searches into 2 categories (which they already do that) such as: NSFW (nudity, porn, brutality) and safe to view pictures. How can ...
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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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Trying to understand VGG convolution neural networks architecture

Trying to understand the VGG architecture and I have these following questions. I understand the general understanding of increasing filter size is because we are using max pooling and so its image ...
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1answer
54 views

Semantic Segmentation For Multiple Objects When Trained On Single Object

More of a conceptual question here: I'm working on semantic segmentation tasks in the medical space using the U-Net. Let's say that I train a U-Net model on medical images with the goal of segmenting ...
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45 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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3answers
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My CNN model performs bad on new (self-created) pictures, what are possible reasons?

I wanted to train a model that recognizes sign language. I have found a dataset for this and was able to create a model that would get 94% accuracy on the test set. I have trained models before and my ...
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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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1answer
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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 ...
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159 views

Can machine learning algorithms be used to differentiate between small differences in details between images?

I was wondering if machine learning algorithms (CNNs?) can be used/trained to differentiate between small differences in details between images (such as slight differences in shades of red or other ...
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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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In a CNN, does each new filter have different weights for each input channel, or are the same weights of each filter used across input channels?

My understanding is that the convolutional layer of a convolutional neural network has four dimensions: input_channels, filter_height, filter_width, number_of_filters. Furthermore, it is my ...
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1answer
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How to classify human actions?

I'm quite new to machine learning (I followed the Coursera course of Andrew Ng and now starting deeplearning.ai courses). I want to classify human actions real-time like: Left-arm bended Arm above ...
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25 views

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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How do I handle large images when training a CNN?

Suppose that I have 10K images of sizes $2400 \times 2400$ to train a CNN. How do I handle such large image sizes without downsampling? Here are a few more specific questions. Are there any ...
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How do we choose the kernel size depending on the problem?

Obviously, finding suitable hyper-parameters for a neural network is a complex task and problem or domain-specific. However, there should be at least some "rules" that hold most times for the size of ...
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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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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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1answer
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Detecting playing cards with a neural network

I want to train an AI to detect playing cards. For that reason I bought many different decks, scanned and labeled them. Next up would be to create training data with an augmentation library. I found ...
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2answers
223 views

How do we classify an unrecognised face in face recognition?

If we have classified 1000 people's faces; how do we ensure the network tells us when it encounters a new person?
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What pre-processing of the image is needed before feeding it into the convolutional neural network?

I can't figure out what preprocessing of the image is needed before feeding it into the convolutional neural network. For example, I want to recognize circles on a 1000 by 1000 px photo. The learning ...
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1answer
1k views

How to detect LEGO bricks by using a deep learning approach?

In my thesis I dealt with the question how a computer can recognize LEGO bricks. With multiple object detection, I chose a deep learning approach. I also looked at an existing training set of LEGO ...
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MNIST Classification code performing with 88%-90% whereas other codes online perform 95% on first epoch

I have been trying to write code to implement plain neural net without convolution from scratch. I took some help online here and added my code to my github account. I don't understand why the ...
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How do i start building an autoclick bot for pubg mobile?

I want to make a bot which clicks the fire button on the mobile screen upon seeing an enemies head. In pubg mobile which is an android game you have to control the fire button and the aim along with ...
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How should I define the loss function for a multi-object detection problem?

I'm trying to create a text recognition project using CNN. I need help regarding the text detection task. I have the training images and bounding box details for them. But I'm unable to figure out ...
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1answer
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Is it legal to construct a public image database (for deep learning) with images from the internet? [closed]

I am trying to put together a public agricultural image database of corn and soybeans, to train convolutional neural networks. The main method of image collection will be through taking pictures of ...
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2answers
379 views

Why is image recognition a key function of AI?

Image recognition, in the context of machine vision, is the ability of software to identify objects, places, people, writing and actions in images. Computers can use machine vision technologies in ...
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1answer
142 views

Is there a simple way of classifying images of size differing from the input of existing image classifiers?

Most image classifiers like Inception-v3 accept images of about size 299 x 299 x 3 as input. In this particular case, I cannot resize the image and lose resolution. Is there an easy solution of ...
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Can I do image classification with Multi Layers Perceptron (MLP)?

I'm seeking guidence here. Can I use Multi Layers Perceptron (MLP), e.g regular flat neural networks, for image classification? Will they perform better than Fisher Faces? Is it difficult to do ...
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Guessing the country given street level photo of buildings/monuments

I have 500-1000 labelled street level photos from which I need to train a model to guess the country. Most photos are of well known areas/landmarks, and I can assume the unseen photos will be similar. ...
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Do Multi-resolution CNN exist?

I am currently working on a problem for which the topographic data is in very different resolution. Let say I have data of 20x20 with 1km2 tiles and also high resolution data of 50m2 tiles. I would ...

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