Questions tagged [image-recognition]

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

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17 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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33 views

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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47 views

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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31 views

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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30 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
29 views

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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21 views

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
110 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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43 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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25 views

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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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
49 views

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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36 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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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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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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25 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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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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3answers
54 views

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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1answer
50 views

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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54 views

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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1answer
27 views

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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45 views

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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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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44 views

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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3answers
110 views

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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1answer
41 views

Can neural network help me with detecting center coordinates of particles in an image?

I have an image of some nano particles that was taken with Scanning Electron Microscope (SEM) attached here. I want to obtain center points coordinates (x,y) for each particle. Doing it by hand is ...
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1answer
50 views

What is a landmark in computer vision?

I guess I understand the concept of face detection, a technique specifies the location of multiple objects in the image, and draws bounding boxes on the target. The question is related to the concept ...
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1answer
54 views

How can I use a Hidden Markov Model to recognize images?

How could I use a 16x16 image as an input in a HMM? And at the same time how would I train it? Can I use backpropagation?
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1answer
55 views

How to perform insect classification given two images of the same insect?

I'm relatively new to image classification. Currently, I am trying to classify insect images, using a convolutional neural network (CNN). When I ask a human expert to identify an insect, I usually ...
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23 views

Training single network for one-shot identification

I am trying to build a face recognition application and I have seen implementations such as dlib. I would like to build a siamese net, and my doubts are about the architecture. Since I am supposed to ...
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1answer
95 views

How can I detect the frame from video streaming that contains a graffiti on city wall?

I am working on a graffiti detection project. I need to analyze data stream from a camera mounted sideways on a vehicle to identify graffiti on city walls and notify authorities with the single best ...
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5answers
114 views

How can I train a neural network to describe the characteristics of a picture?

I have collected a set of pictures of people with a text explaining the characteristics of the person on the picture, for example, "Big nose" or "Curly hair". I want to train some type of model that ...
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1answer
65 views

Image dataset for pomegranate plant disease

I am implementing a project on pomegranate plant disease in Machine learning. I want a dataset of all kind images of a healthy and unhealthy part of the pomegranate plant. I got a dataset from ...
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2answers
79 views

Is there any difference between the convolution operation applied to images and applied to other numerical 2D data?

Is there any difference between the convolution operation applied to images and applied to other numerical 2D data? For example, we have a pretty good CNN model trained on a number of $64 \times 64$ ...
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1answer
41 views

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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1answer
40 views

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
65 views

Should I apply image processing techniques to the inputs of convolution networks?

After working for some time with feature-based pattern recognition, I am switching to CNN to see if I can get a higher recognition rate. In my feature-based algorithm, I do some image processing on ...
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1answer
52 views

Reinforcement-learning: grey-scaling vs color of CNN input. Tradeoff?

I'm doing reinforcement learning and have a visual observation as state input for my agent. In the Deepmind Atari paper they greyscale the input image before they input it into the CNN to reduce the ...
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1answer
31 views

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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Image-to-Image Regression for GO territory classification

I'm trying to implement a neural network that is able to generate an image indicating territory occupation given a board state for GO (a strategy board game). Input images are 19x19x1 grayscale images,...
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1answer
2k views

Tensorflow-gpu cannot use Nvidia GPU with CUDA

I'm working on a Python Keras/Tensorflow image recognition script (on Ubuntu 18.04) which works ok, but it will only train on CPU (which is slow) and I want to be using my GPU (i have a Nvidia Geforce ...
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Training dataset for convolutional neural network classification - will images captured on the ground be useful for training aerial imagery?

I am an agronomy graduate student looking to classify crops from weeds using convolutional neural networks (CNNs). The basic idea that I am wanting to get into involves separating crops from weeds ...
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1answer
55 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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1answer
28 views

Recognizing Set CARDs

Set is a card game and is Nicely described here. Each set-card has 4 properties: The number(1,2 or 3) the color (Red, Green or Purple) Fill (Full, Stripes, None) Form (Wave, Oval or Diamond) ...
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1answer
74 views

Is it expected that adding an additional hidden layer to my 3-layer ANN reduces accuracy significantly?

I've been using several resources to implement my own artificial neural network package in C++. Among some of the resources I've been using are https://www.anotsorandomwalk.com/backpropagation-...

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