Questions tagged [optical-character-recognition]
For questions about the application of AI/ML algorithms in the field of optical character recognition (OCR), aka optical character reader (OCR), which is the mechanical or electronic conversion of images of typed, handwritten, or printed text into machine-encoded text.
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Unexpected AI platform help manage breach [closed]
Someone deployed AI platform to add over the tinnitus.
The AI IP is not accessible to me, and it is linked to a union/ organization that experiments with it causing augmentation on the involuntary ...
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Where would If my goal was to do OCR pdf text extraction on 1000s of PDFs I have?
So I have lots of data (pdfs) that I want to train an AI model to extract info from. All of them are a little different but have the same key data points. Is it possible to train an AI on the pdfs I ...
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True way to pad input image for Transformer OCR model?
I have a Transformer model for OCR problem. I would like to resize input image while keeping image ratio. How should I do? (I prefer 1 but I have not tried yet)
Keep width fit to new width, scale ...
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Would it be a problem to use non-squared images for a CNN model?
I want to create a music sheet scanner using CNN Model and the images I am using are not squared and, if I make them squared, important data will be lost and it might confuse the model.
Is it ok to ...
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Can AI/ML be used to decipher unknown text on such a low resolution scale of one or two letters to a pixel by color?
Can an image of unknown text, with resolution of about one or two letters in real life represented by a pixel (like if the image is a photo taken from far away), be used by machine learning or AI to ...
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How to identify patterns of errors in text recognition
I have a text recognition model that takes an image of a word as input and I want to identify if there are any specific patterns in the prediction that it consistently gets wrong.
I assume there must ...
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How are OCR training datasets constructed?
For the sake of concreteness: let's suppose that the word "OCR" refers to any OCR system build on an R-CNN architecture. Similarly, in aims of simplicity, let's declare that we are ...
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How to improve the performance of Easy OCR
I am working on a project that requires me to identify a product on a grocery shelf. For that, I am trying to use test recognition and localization to spot a product.
I tried Easy OCR and tesseract ...
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Effective fast mobile ocr model
I plan to develop OCR application which is mobile oriented and fast. (like 10~30 fps) The images that will be detected is not wild images. They are refined data such as cell phone capture images. In ...
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Concise and mathematically-oriented book on AI and neural networks suitable as a gift [closed]
I would like to buy a book about AI and neural networks written on accessible level for a 17 years old mathematically very gifted student interested in these topics. The book should contain some ...
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Which AI techniques are there that combine multiple models to make sense of data at different stages?
I have been working to design a system that uses multiple machine learning models to make sense of data that is dynamically webscraped. Each AI would handle a specific task, for example:
An AI model ...
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Why object detection algorithms are poor in optical character recognition?
OCR is still a very hard problem. We don't have universal powerful solutions. We use the CTC loss function
An Intuitive Explanation of Connectionist Temporal Classification | Towards Data Science
...
user40943
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In OCR, how should I deal with the warped text on the sides of oval objects?
Consider an image that contains one can (or bottle, or any similar oval object), which has texts all over it. In the image below, I have many bottles, but you can assume that each image only contains ...
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What are the disadvantages to using a distance metric in character recognition prediction
I am reading this paper, that is discussing the use of distance metrics for character recognition predicton.
I can see the advantages of using a distance metrics in predictions like character ...
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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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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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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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OCR - Text recognition from Image
I plan to develop OCR application using tensorflow to get the value from the image. Text in the image may handwritting or text printed.
From the image, my ocr appplication will able to get the value ...
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How can I detect diagram region and extract (crop) it from a research paper [closed]
How can I detect diagram region and extract(crop) it from a research paper
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How can I recognise the name of a molecule given an image of its structure?
I want to recognize the name of the chemical structure from the image of the chemical structure. For example, in the image below, it is a benzene structure, and I want to recognize that it is benzene ...
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Is there a deep learning-based architecture for digit localisation?
I'm new to object detectors and segmentation. I want to localize digits on a plate as fast as possible. All images of the dataset are normalized to $300 \times 60$. There are different approaches to ...
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Generate credit cards dataset for locating number region
Currently I'm working on a project for scanning credit card and text extraction from cards. So first of all I decided to preprocess my images with some filters like thresholding, dilation and some ...
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Is there any way to classify Document Image without OCR? [closed]
I have multiple invoices images which need to classify invoice types such as fright, utility, goods, etc. Is there any way to classify without OCR?
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How can we recognise musical notes in low-resolution or blurry images?
I was looking for an approach to recognise musical notes from photos.
I found this repository https://github.com/mpralat/notesRecognizer. However, it doesn't seem good enough. If you look into the <...
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Attempting to solve a optical character recognition task using a feed-forward network
I am doing some experimentation on neural networks, and for that I am trying to program a plain OCR task. I have learned CNNs are the best choice ,but for the time being and due to my inexperience, I ...
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How does a neural network output text box location data?
I'm interested in creating a convolutional neural network or LSTM to locate text in an image. I don't want to OCR the text yet, just find the text regions. Yes, I know Tesseract and other systems can ...
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Is it possible to use AI to denoise noisy documents?
I have some documents containing some text (machine writing text) that I intend to apply OCR on them in order to extract the text.
The problem is that these documents contain a lot of noise but in ...
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zonal or template ocr invoices reading
I'd like to explore the possibilities of applying artificial intelligence to ocr reading.
Basic ocr invoices processing let me convert 30% of them only.
The main purpose is defining invoices areas by ...
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How much extra information can we conclude from a neural network output values?
Consider I have a 3 layers neural network.
Input Layer containing 784 neurons.
Hidden layer containing 100 neurons.
Output layer containing 10 neurons.
My objective is to make an OCR and I used ...
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How could I use machine learning to detect text and non-text regions in scanned documents?
I have a collection of scanned documents (which come from newspapers, books, and magazines) with complex alignments for the text, i.e. the text could be at any angle w.r.t. the page. I can do a lot of ...
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Effective algorithms for OCR
I am using Google's OCR to extract text from images, like receipts and invoices.
Whare examples of techniques used to make sense of the text? For example, I would like to extract the date, name of the ...
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How should the racing agent take into account the velocity of the vehicle, given the images with a speedometer?
I'm developing a game AI, which tries to master racing simulations. I already trained a CNN (AlexNet) on in-game footage of me playing the game and the pressed keys as the target. As the CNN is only ...
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Why can't OCR be perceived as a good example of AI?
On the Wikipedia page about AI, we can read:
Optical character recognition is no longer perceived as an exemplar of "artificial intelligence" having become a routine technology.
On the other hand, ...
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Are there any textual CAPTCHA challenges which can fool AI, but not human?
Are there any modern techniques of generating textual CAPTCHA (so person needs to type the right text) challenges which can easily fool AI with some visual obfuscation methods, but at the same time ...
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What are the challenges for recognising the handwritten characters?
This 2014 article saying that a Chinese team of physicists have trained a quantum computer to recognise handwritten characters.
Why did they have to use a quantum computer to do that?
Is it just for ...
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