# Tag Info

Accepted

### What is meant by the term "prior" in machine learning

Put simply, and without any mathematical symbols, prior means initial beliefs about an event in terms of probability distribution. You then set up an experiment and get some data, and then "update" ...
• 9,837
Accepted

### Normalized measure from dynamic time warping

Sure. There's a straightforward way to convert an unnormalized distance metric into a normalized similarity measure. Basically, use $$S(x,y) = \frac{M - D(x,y)}{M},$$ where $D(x,y)$ is the ...
• 159k
Accepted

### What method of collective recogintion to use for digits recognition?

The state of the art for digit recognition does not use collective recognition, competence areas, ensembles, or any of the other ideas you propose in your question. Instead, the state of the art for ...
• 159k
Accepted

### What is a good approach to symbol identification/recognition given a path, instead of raster data

What you are looking for is called "on-line recognition". I have written my Bachelors thesis about this: Thoma, Martin. "On-line Recognition of Handwritten Mathematical Symbols." arXiv preprint ...
• 2,360
Accepted

### How does continuous computer vision works?

It depends on what you're recognizing, but I'm familiar with two basic techniques: Apply the recognition algorithm to each frame of the video. Be fast enough that you can run on every frame of video....
• 159k

### Machine Learning: Identify Patterns in Time-Series Data

Yes, your data is "time-series data", since it's a sequence of measurements of the same variable collected over time. Time-series data can be collected continuously or at discrete intervals. Your ...
• 1,624
Accepted

### Which algorithm for counting the occurrences of a certain pattern (spots) in an image?

The best way to get an orientation is to read a textbook on computer vision or image processing. There are lots of techniques known, and that's often the best way to get an introduction to a broad ...
• 159k

### Extracting features for texture classification

If it is important for you to get a high accuracy, then use a convolutional neural network (ConvNet). These ConvNets hold the state of the art for most visual recognition tasks. If your training set ...
• 131

### Automated lip-reading: inferring what someone is saying, based upon video of them speaking

There is some recent work here: LipNet: Sentence-Level Lipreading. Yannis M. Assael, Brendan Shillingford, Shimon Whiteson, and Nando de Freitas. They achieve 93% accuracy on a corpus of 3-second ...
• 159k
Accepted

### deterministic finite automaton for "does contain substring $w$" is of linear size

Consider the following NFA: the states are $q_0,\ldots,q_{|w|}$, there are transitions $q_{i-1} \to q_i$ on $w_i$, there are self-loops on $q_0,q_{|w|}$ (for all alphabet symbols), the initial state ...
• 277k
Accepted

### Where I can I find Pre Trained CNN Datasets for Facial Emotion Recognition?

You are probably interested in IAPS, and want to read Analysis of Physiological Signals for Emotion Recognition Based on Support Vector Machine. But to be honest this classification is doomed in ...
• 9,455
Accepted

### how to identify patterns in program execution flows?

There's probably no existing turnkey solution that will do what you want, out of the box. I suspect this would be a research-level task, so you might want to start by searching the research ...
• 159k
Accepted

### Efficiently find smallest unique substring

You can try suffix array approach which find all suffix of a given string of length n in O(n) time. There are many algorithm to construct suffix array from a given input string. Look at complete ...
• 119

### What is meant by the term "prior" in machine learning

It's roughly any pre-training choices you encode into your model In machine learning a prior is, according to the book "Deep Learning" by Goodfellow, Bengio, and Courville, a probability ...
• 121
Accepted

### Finding (and possibly extracting) source code in heterogenous text data set

There are many possible ways you might do this. I'll suggest one. I suggest you train a classifier to recognize whether a sequence of characters is code or text. Here, the goal is to build a ...
• 159k
Accepted

### reverse string to pattern matching

The Shortest Levenshtein's Distance should be good enough. See if this Matching Wildcards Wikipedia page can be of help.

### Recognizing a trajectory from a set

The Fréchet distance is a similarity measure for trajectories that often works well for curves that we consider visually similar. However, it is not scale or translation invariant, because it compares ...
• 8,248

### A pretrained model for mathematical equations characters detection

Detexify is a service that recognizes LaTeX symbols from handwritten figures. Their training dataset is freely available on Github.
• 8,248
Accepted

• 81.7k
1 vote

### Trying to detect recurring events at certain intervals, e.g. daily, weeekly, monthly, annually

Given an event type and a sequence of times at which it has occurred, there are several ways to check whether it seems to recur periodically. One simple approach is to look at the interarrival times (...
• 159k
1 vote

### Efficiently find smallest unique substring

I can suggest a simple method that will achieve this in many practical cases in linear time, for example if you examine "War and Peace", but will fail if some characters are very common. Assume the ...
• 30k
1 vote

### What is meant by the term "prior" in machine learning

In Bayesian statistics, a "prior" represents the beliefs we have before observing some data. Then, after we observe some data, we update our beliefs; those updated beliefs are called the &...
• 159k
1 vote

### Changing Rabin-Karp without modulo to Rabin-Karp with modulo

Don't wait to do the modular reduction at the end. Every time you do an addition or multiplication, immediately reduce modulo the modulus. This keeps all intermediate results small.
• 159k
1 vote
Accepted

### Simple Recognition Algorithm, How Does It Work?

Normally we build a classifier that accepts images of a fixed size: say, 100x100 pixels. Given an image that is larger than that, we re-scale it to 100x100 pixels before feeding it into the ...
• 159k
1 vote

### Which algorithm for counting the occurrences of a certain pattern (spots) in an image?

First thing, you must be clear about the pattern because computer vision has still focused on pattern specific algorithms. If I consider your pattern is circularity if I am not wrong you are asking ...

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