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Questions tagged [image-recognition]

For questions about the image-recognition abilities of AI.

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Human Pose Comparison

I'm trying to create a service which compares 2 human poses as a part of my main application. I managed to plot skeletons on the images using OpenPose. A detailed explanation of my question: I have 2 ...
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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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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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Is it possible to make a 'forked path' neural network?

I want to make a network, specifically a CNN for image recognition, that takes an input, processes it the same way for several layers, and then at some point splits before coming to two different ...
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How do I denoize a microscopic image?

I'm working in a computer vision project, where the goal is to detect some specific parasites, but now that I have the images, I noticed that they have a watermark that specifies the microscope ...
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1answer
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CNN output generally has more than one category in one-hot categorization?

I'm a bit of a CNN newbie, and I'm trying to train one to image classify pictures of pretty similar looking particles. I'm making the inputs and labels by hand from a set of 48x48 grayscale images, ...
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Algorithms to indentify people in pictures without using face recognition

There are lot of researches about face detection in pictures, but is it the only way one can say "this person I'm looking for is here in this picture"? Aren't there algorithms that you can provide ...
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Double Convolution Layers in Yolov3

Lately, I have been working on yolov3 and have been trying to train it on x-ray images to detect a fracture. However, I have decided that I would want to increase the number of convolution layers for ...
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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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An approach on reading musical notes from photos

I was looking around, a promising approach was this: https://github.com/mpralat/notesRecognizer the problem is: it doesn't seem good enough. One should be able to read musical notes with lower ...
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1answer
29 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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1answer
54 views

Why doesn't my image classification network get better with training?

I am attempting to train a network to do something I thought would be a relatively simple case to learn with: identify whether the back of a scanned vintage postcard has one of 'no postage stamp', a '...
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Siamese Network for unknown object

I am currently trying to create a One-Shot network using the Siamese architecture for an object that isn't a face. My problem is, in normal Face Recognition the detecting gadget (e.g. Smartphone) ...
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32 views

Count number of objects in image using CNN

I'm looking for neural network architecture that excel in counting objects. For example, CNN that can output the number of balls (or any other object) in a given image. I already found articles about ...
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How does the process of segmentation of face in face recognition work?

How does the process of segmentation of face, using a CNN, in face recognition, work? How are we able to segment the face?
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1answer
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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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Presence of object (highly occluded vehicle) in a scene

How to detect presence of object (highly occluded) in a scene? There are specific features (small patterns, etc), which allow to say that object is present, but it is not enough for detection for ...
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Mimicking certain human functions

Is it a common practice to do 3-dimensional imagary data acquisition and implementing the dataset to certain high resolution motor driven humanoid candidates to mimic the human micro expressions or ...
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1answer
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Mnist CNN Architecture

In this tutorial from Jeremy Howard: What is torch.nn really? he has an example towards the end where he creates a CNN for mnist. In nn.Conv2d he makes the ...
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Bubble Chamber Image Analysis Using Neural Network

I have a data analysis problem that I can reduce to one similar to analyzing the trajectories in the images below. These images show the tracks of subatomic particles interacting in a bubble chamber. ...
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How to annotate a teleoperated robot?

Most robotics challenges like Robocup soccer, micromouse and the Amazon picking challenge are oriented on fully autonomous systems. A motion controller gets started, the operator takes away his hands ...
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2answers
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Deep Ranking/Best way to classify book covers?

I recently came across a paper on Deep Ranking. I was wondering whether this could be used to classify book covers as book titles. (For example, if I had a picture for the cover of the second HP book, ...
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Deep Learning on how to find out the body measurement (e.g. shoulder length, waist, hips, legs length etc) from mobile camera captured images?

I do understand that there are plenty of mobile apps available for body measurement (e.g. MTailor) or creating 3D model (3dlook). What I would like to find out is how we can use deep learning to ...
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1answer
59 views

What's the commercial usage of “image captioning”?

If "image captioning" is utilized to make a commercial product, what application fields will need this technique? And what is the level of required performance for this technique to be usable?
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How do I make AI based object picker?

I want to develop an AI based object (mainly toy) picker that can clean my kid's room and put toys in toy basket. Can somebody help me how to acheive this? I want to make a custom solution so that it ...
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1answer
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Pixel-Level Detection of Each Object of the Same Class In an Image

I have source data that can be represented as a 2D image of many similar curves. They may oftentimes cross over one another, so regions of interest will overlap. My goal is to implement a neural ...
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Can machine learning algorithms (CNNs?) be used/trained 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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Measuring Width of Crack

Are there any projects where you can detect and measure the width of a crack? I am using tensorflow and labeling the data sets for now.
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1answer
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Is it possible to spot photoshoped or edited photos using AI?

I have this question in my head: does the current level of AI development allow us to spot faked or photoshoped images? (i.e forged ID card or personal documents). If it is possible, what is such a ...
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1answer
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Smaller interest area for images than the size of the image in classification neural networks

I have the following binary classification problem, my labeled dataset contains images 96x96 px. Now in every image the interest area is of size 32x32 px in the center of the image, and the images are ...
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51 views

What are some of the drawbacks of one-shot learning?

One-shot learning seems to work really well in many application domains. Are there any major (or even minor) drawbacks of using one-shot learning? Does it have flaws that could prevent it from being ...
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2answers
86 views

How to approach this handwritten digit recognition?

I have multiple pictures that look exactly like the one below this text. I'm trying to train CNN to read the digits for me. Problem is isolating the digits. They ...
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1answer
60 views

Recognition of small objects

I'm currently implementing an Android app for street sign recognition. My solution works quite well for the GTSRB dataset, since it provides a labeled test set of centered images. However, it doesn't ...
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Geometry shape identification and vertex/side label association

I want like to be able to draw a shape outline e.g. (pen and paper) triangle, square, circle.. then label the vertices and sides And have ML identify the shape and the symbol associates with each ...
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How a game playing agent could identify potential objects and proximity?

Most implementations I'm seeing for playing games like Atari (usually similar to DeepMind's work using DQN) have 4 graphical frames of input fed into 3 convolutional layers which are then fed into a ...
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How to preprocess a modified dataset so that a fitted CNN makes correct predictions on an un-modified version of the dataset?

for a school project I have been given a dataset containing images of plants and weeds. The goal is to detect when there is a weed in the pictures. The training and validation sets have already been ...
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2answers
527 views

Which AI tool for food recognition?

I'm working in a company that opens restaurants in enterprises. Every day at lunch, we want our clients to be able to scan their trays, sothat the food is detected automatically thanks to AI / image ...
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1answer
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Image prediction model when data-set classes have visual similarity

Lets say we have a data-set of all cats and we have to identify the cat breed based on given test image. As, the two different cat breeds have visual similarity can we use existing networks (VGG, ...
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1answer
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Feature learning vs feature engineering vs feature learning and engineering

With the advancement of deep learning and a few others automated features learning techniques, manual feature engineering started becoming obsolete. Any suggestion on when to use manual feature ...
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1answer
64 views

Are Computer Vision and Digital Image Processing part of Artificial Intelligence?

There are some fields of Computer Vision that are similar to Artificial Intelligence. For example, pattern recognition and path tracking. Based on these similarities, can we say that the Computer ...
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1answer
40 views

Influence of location on a Neural Network trained for parking detection occupancy

I loaded a neural network model trained with Caffe by other people in OpenCV. The model should detect the presence of a car in a single parking spot outputting the probability of it being free/...
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1answer
58 views

How to measure the reasoning capabilities of neural networks

Which possibilities exist to evaluate the visual reasoning capabilities of neural networks in the field of image recognition? Are there methods to measure the ability of machine reasoning? Or ...
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1answer
252 views

How can we use data augmentation for creating data set for face recognition and will the inverted faces on augmented images detected?

I saw when browsing we can use data augmentation for creating a dataset for face recognition. The augmented images may include inverted, tilted or distorted faces. Do the model detect the face from ...
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1answer
51 views

What is a good descriptor for similar objects?

I am developing an image search engine. The engine is meant to retrieve wrist watches based on the input of the user. I am using SIFT descriptors to index the elements in the database and applying ...
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How to use Machine Learning to create a “Draw-A-Person Test”

The process revolves around a child's drawing. Each part of each drawing corresponds to a score as in the Draw a Person Test conceived by Dr. Florence Goodenough in 1926. The goal of the machine is to ...
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Is 1mb an acceptable memory size for images being trained in a CNN?

I am using Tensorflow CNN to build an image classification/prediction model. Currently all the images in the dataset are each about 1mb in size. Most examples out there use very small images. The ...
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1answer
44 views

how image segmentation evaluated?

I implemented the segmentation on my DICOM Dataset and it is compared with manual segmentation to find the accuracy of segmentation, is there other methods for evaluation?
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1answer
59 views

how to segment each part in dicom image?

As i'm beginner in image processing,having difficulty in segmenting all the parts in dicom image.currently i'm applying watershed algorithm but it segment only that part that have tumor.i have to ...
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4answers
125 views

Using Convolutional Neural Networks for movement classification

I have programmed my first network for the MNIST dataset. I was wondering what the first approach would be to recognize certain movements. I have read about that the time dimension should be ...