Questions tagged [image-recognition]

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

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82
votes
9answers
6k views

How is it possible that deep neural networks are so easily fooled?

The following page/study demonstrates that the deep neural networks are easily fooled by giving high confidence predictions for unrecognisable images, e.g. How this is possible? Can you please ...
26
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8answers
4k views

Is there any research on the development of attacks against artificial intelligence systems?

Is there any research on the development of attacks against artificial intelligence systems? For example, is there a way to generate a letter "A", which every human being in this world can recognize ...
25
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4answers
415 views

Is the pattern recognition capability of CNNs limited to image processing?

Can a Convolutional Neural Network be used for pattern recognition in problem domains without image data? For example, by representing abstract data in an image-like format with spatial relations? ...
23
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3answers
39k views

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 ...
15
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2answers
9k views

How to implement an "unknown" class in multi-class classification with neural networks?

For example, I need to detect classes for MNIST data. But I want to have not 10 classes for digits, but also I want to have 11th class "not a digit", so that any letter, any other type of ...
10
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3answers
571 views

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 ...
10
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4answers
402 views

What are some tactics for recognizing artificially made media?

With the growing ability to cheaply create fake pictures, fake soundbites, and fake video there becomes an increasing problem with recognizing what is real and what isn't. Even now we see a number of ...
9
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1answer
361 views

How much of a problem is white noise for the real-world usage of a DNN?

I read that deep neural networks can be relatively easily fooled (link) to give high confidence in recognition of synthetic/artificial images that are completely (or at least mostly) out of the ...
8
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2answers
255 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 ...
8
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1answer
155 views

Can a single neural network handle recognizing two types of objects, or should it be split into two smaller networks?

In particular, an embedded computer (with limited resources) analyzes live video stream from a traffic camera, trying to pick good frames that contain license plate numbers of passing cars. Once a ...
7
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5answers
2k views

How can action recognition be achieved?

For example, I would like to train my neural network to recognize the type of actions (e.g. in commercial movies or some real-life videos), so I can "ask" my network in which video or movie (and at ...
7
votes
1answer
183 views

How good is AI at generating new, unseen [visual] examples?

By new, unseen examples; I mean like the animals in No Man's Sky. A couple of images of the animals are: So, upon playing this game, I was curious about how good is AI at generating visual ...
7
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2answers
3k views

Does data skew matter in classification problem?

I'm working on an image classification problem using a neural network. In the training data set, 90% of the samples fall into 10% of all categories, while 10% of the sample fall into the other 90% ...
7
votes
2answers
6k views

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 ...
7
votes
1answer
131 views

What algorithms are used for image segmentation of images where objects are not composed of pixels that are similar in value?

In the process of segmentation, pixels are assigned to regions based on features that distinguish them from the rest of the image. Value Similarity and Spatial Proximity, for example, are two ...
6
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2answers
167 views

Is algorithmic bias due to the training dataset used?

I recently read about algorithmic bias in facial recognition. Is algorithmic bias due to the training dataset used, or is it due to something else?
6
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1answer
3k 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 ...
5
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2answers
391 views

How can I train a neural network for image classification when the dataset is small?

I need to train a convolutional neural network to classify snake images. The problem is that I have only a small number of images available for some snake types. So, what is the best approach to train ...
5
votes
1answer
208 views

Are there any microchips specifically designed to run ANNs?

I'm interested in hardware implementation of ANNs (artificial neural networks). Are there any popular existing technology implementations in form of microchips which are purpose designed to run ...
5
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3answers
213 views

How to make convnets aware what the image actually is, not what is depicted on it?

I've uploaded a picture to Wolfram's ImageIdentify of graffiti on the wall, but it recognized it as 'monocle'. Secondary guesses were 'primate', 'hominid', and 'person', so not even close to 'graffiti'...
5
votes
1answer
161 views

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 ...
5
votes
1answer
70 views

Do models train better if the labelling information is more specific (or dense)?

I'm working on a project where there is a limited dataset of videos (about 200). We want to train a model that can detect a single class in the videos. That class can be of multiple different types of ...
5
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1answer
2k views

How are the kernels initialized in a convolutional neural network?

I am currently learning about CNNs. I am confused about how filters (aka kernels) are initialized. Suppose that we have a $3 \times 3$ kernel. How are the values of this filter initialized before ...
5
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1answer
174 views

Is it feasible to train a Machine Learning Model (with image inputs) in an average personal computer?

There are lots of examples of machine learning systems that can recognize objects and extract other information from images with very high precision. To train the models of such systems is necessary (...
5
votes
1answer
903 views

How do I combine models trained on different data to increase classification accuracy?

I have two trained models. One is using a LinearSVC algorithm and is trained on numerical data from medical examination from patients with diabetic retinopathy. The second one is a neural network ...
5
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1answer
1k views

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 ...
5
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2answers
263 views

Variable Number of Inputs to Neural Networks

So suppose that you have a real estate appraisal problem. You have some structured data, and some images exterior of home, bedrooms, kitchen, etc. The number of pictures taken is variable per ...
5
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3answers
2k views

Are Convolutional Neural Networks better than existing image recognition libraries that don't use CNNs?

Are Convolutional Neural Networks summarily better than pattern recognition in all existing image processing libraries that don't use CNN's? Or are there still hard outstanding problems in image ...
5
votes
2answers
77 views

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 ...
5
votes
2answers
299 views

How can I use Neural Network in motion identification

I'm quite new to image processing and AI. But I have the expertise to create a network that can be used in object detection and recognition. Most of the time I've used ANN or Naive Bayes. Now, I want ...
4
votes
1answer
2k views

Is the QuickDraw with Google neural net a convolutional neural network?

Does anyone know, or can we deduce or infer with high probability from its characteristics, whether the neural network used on this site https://quickdraw.withgoogle.com/ is a type of convolutional ...
4
votes
3answers
2k 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 ...
4
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2answers
198 views

As a starter: what is the form of training data for image processing

What we are doing in the image processing training. We are storing some form of data which is going to act as the knowledge or experience of the system. In which form can the system store it's ...
4
votes
2answers
143 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 $64 \times 64$ ...
4
votes
2answers
472 views

Viola Jones Algorithm

Can Viola Jones algorithm be used to detect the facial emotion. Actually it was used in creating harr-cascade file for object and facial detection, but what confused me is whether it can be used to ...
4
votes
3answers
15k views

How to "combine" two images for CNN input (classification task)?

For a classification task (I'm showing a pair of exactly two images to a CNN that should answer with 0 -> fake pair or 1 -> real pair) I am struggling to figure out how to design the input. At the ...
4
votes
1answer
41 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) ...
4
votes
1answer
88 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-...
4
votes
1answer
66 views

Optimizing image recognition results for unknown labels

I’m training a network to do image classification on zoo animals. I’m a software engineer and not an ML expert, so I’ve been retraining Google’s Inception model and the latest models is trained ...
4
votes
1answer
43 views

How do we perform object classification given images from a camera that captures images at 15 FPS?

I've been working with vanilla feedforward neural networks and have been researching the convolutional neural network literature. If a camera is capturing a video at a rate of 15 frames per second, is ...
4
votes
1answer
190 views

How to identify the face of a certain customer in a grocery store?

How would you solve the problem of identifying certain customer in a grocery store? Suppose our client is already signed-up on our website with an unique ID given to him. To come in to the store, ...
4
votes
1answer
390 views

Get the position of an object, out of an image

I have some images with a fixed background and a single object on them which is placed, in each image, at a different position on that background. I want to find a way to extract, in an unsupervised ...
4
votes
1answer
84 views

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 ...
4
votes
1answer
53 views

How to compare the training performance of a model on different data input?

So I have a deep learning model and three data sets (images). My theory is that one of these data sets should function better when it comes to training a deep learning model (meaning that the model ...
4
votes
1answer
2k views

Reading a value of a real gauge

I have a simple gauge displaying analog values ranging from 0 to 4. Here is an image of the gauge. Unfortunately there is no way to get a analog or digital signal for the value. How do I read the ...
4
votes
1answer
809 views

Image comparison algorithm, trying to figure out how similar two "binary" forms are

I'm a student I'm completely new to this technology maybe my approach could be completely wrong, I want to create an algorithm that compares the similarity between two binarized images. I'll explain: ...
4
votes
1answer
104 views

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 ...
4
votes
0answers
41 views

How can I improve the performance of a model trained to detect vehicle poses?

I'm looking for some suggestions on how to improve our vehicle image recognition. We have an online marketplace where customers submit photos of their vehicles. The photos need to meet certain ...
4
votes
0answers
47 views

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 ...
3
votes
1answer
77 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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