15 votes
Accepted

Using AI to extend an imagine pattern

As Edoardo says in their excellent answer, the task at hand can be approached as an outpainting problem and there's some great tools available to do this. To throw an alternative into the ring, I'd ...
9 votes

Using AI to extend an imagine pattern

The task you would like to accomplish is referred to as "outpainting". See example below. Very recently, OpenAI released an outpainting feature that extends the possible operations to ...
7 votes
Accepted

What artificial intelligence strategies are useful for summarization?

The following post has a bit of math, which I hope helps to explain the problem better. Unfortunately it seems, this SE site does not support LaTex: Document summarization is very much an open ...
  • 1,134
5 votes

How can I use neural networks for detecting TV channel logos in video frames?

To perform image recognition you have to find a way to represent an image with certain features. One of the defining characteristics of a good image recognition algorithm are it's ability to detect ...
  • 1,146
4 votes
Accepted

What approach should I use to detect faces in video game footage?

At first, you can find lots of information as pedestrian detection. As you are trying to localize game characters, the face is not the best option. You need to look for the character in general. ...
3 votes

Use mobile device camera for moving pattern recognition

Firstly, before we commence I will recommend that you refer to similar questions on the network i.e. https://stackoverflow.com/questions/6499880/ios-gesture-recognition-utilizing-accelerometer-and-...
  • 1,146
3 votes
Accepted

Is music/sound similarity comparison feasible on neural networks?

Yes, it is possible, even if the best approach could be different from neural networks. Anyway, you should extract some significant features from the audio (energy, onsets, root frequencies, and ...
  • 146
3 votes

Detect street and sidewalk surface in aerial imagery (neural network)

Yes, in fact neural networks (NNs) are very efficient at segmentation and it seems to me that your problem matches the capabilities of neural networks very well. I think it best for you to truly ...
  • 450
3 votes
Accepted

How to achieve recognition of postures and gestures?

Just to add some discourse; this is actually an incredibly complex task, as gestures (aka kinematics) function as an auxiliary language that can completely change the meaning of a sentence or even a ...
2 votes

What would the commercial application of a conscious AI look like/be?

They may be just for fun. If you had a robot that understood you, could hold a conversation with you about your interests, and even had goals of its own (good or bad), it wouldn't really need to do ...
2 votes

What are some techniques/method that can be used to train and detect objects like cars and humans?

The terms you are looking for are deeplearning and convolutional neural networks for object detection. Google responds well to these terms. From academical point of view you can start from: Single ...
2 votes

Which machine learning algorithm can be used to identify patterns in a dataset of the cache performance of a CPU?

You're basically looking for is unsupervised learning (UL). There are a lot of UL techniques around, but I'm not sure you'll find one that does exactly what you want with no user input at all. Still, ...
  • 3,697
2 votes

how to recognise handwriting and convert into text?

What you described sounds to me like Optical Character Recognition(OCR). If you want to implement your own, I would say read through how an open source OCR like Tesseract was implemented. ...
2 votes
Accepted

Is there a way to perform pattern recognition without a labeled training set?

You should look into unsupervised learning, which is machine learning without a human-labeled training set.
2 votes

Using neural network to recognise patterns in matrices

Would I be right in saying that this becomes a sort of 'pattern recognition' problem? Technically, yes. In practice: no. I think you might be interpreting the term "pattern recognition" a bit too ...
2 votes

Image recognition service architecture

That is one of the good example for research. Personally, I prefer to segment out all the desired outputs at once. Then, check the success rate. If you cannot hit the success rate that you desire, you ...
2 votes
Accepted

Will training an AI still work if the input data is somewhat sparse?

First, the title mentions "sparse data". Recently the expression has taken a clear meaning: The agent input is data with mostly zeros. In the question a different meaning: A "sparse data stream", ...
  • 1,490
2 votes

What are some tactics for recognizing artificially made media?

Digital Media Forensics (DMF) field aims to develop technologies for the automated assessment of the integrity of an image or video, so DMF is the field you are looking for. There are several ...
  • 35k
2 votes
Accepted

How can AI be used to more reliably analyze and plan around the tie between climate and emissions?

Can AI provide a more reliable analysis of the gross effects of carbon emissions on extinctions of species ice-cap melting, and other effects? Yes. The work of Judea Pearl and others over the last 20 ...
2 votes

How could I use machine learning to detect text and non-text regions in scanned documents?

TextDetector, Tesseract and other open source packages implement text detection (object detection for text). There's also a pretrained Tensorflow model that does text detection. A text detector will ...
  • 151
2 votes

Finding anomaly detection by pattern matching in a set of continous data

Without knowing the kind of data and the process generating it it's hard to give a definite answer. In general, I would attempt a network that has as inputs the actual sensor readings, and outputs the ...
2 votes

Finding anomaly detection by pattern matching in a set of continous data

Instead of using a neural network, simply sample as many non-anomalous readings from each sensor as you can. If the distribution of the readings from each sensor is approximately normal (check the ...
  • 583
2 votes

Is there a machine learning algorithm to find similar sales patterns?

I would recommend a hierarchical cluster algorithm, after normalising your numbers into proportions. Then the clustering should be able to identify similar patterns. Depending at which level you make ...
  • 5,167
2 votes
Accepted

Is there a machine learning algorithm to find similar sales patterns?

If I understand correctly you want to find companies with similar patterns to yours. I would start with measuring cosine similarity between your company and ...
  • 206
2 votes

Neural networks for sports betting

This is probably not going to work well as a way to make money. People with far larger budgets, and far more training, are already milking out any money to be made this way. This is probably their day ...
2 votes

How to detect patterns in salary distribution if we are suspecting malicious distribution based on employee's region?

A simple initial approach would be to separate it by position and check for each: Use linear regression: $\hat{salary} = \sum_i \alpha_i * \hat{region}_i + \sum_k \beta_k * \mathbf{1}[\hat{gender}=k]$...
  • 2,309
2 votes
Accepted

When labelled data is not available, what are some common unsupervised learning algorithms for pattern recognition that can be used?

There are some unsupervised learning algorithms that can be used for pattern recognition (i.e. the discovery of patterns in data). The most notable one is probably k-means, which is a clustering ...
  • 35k

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