# Tag Info

4

This looks like what pretty "classical" video compression does when facing severe data loss – notice the very MPEG-typical square blocks, and how some of the probably more changing blocks are getting "updates" in your still? That's because, although the last reference frame was lost, the decoder tries its best to reconstruct an image ...

3

Is there a script / tutorial / demo for penis detection? [...] Fairly serious quesion, future of internet memes is at stake Yes, there is. Common Pattern Recognition techniques will be able to spot one even with what would be considered today "traditional" approach (i.e. without "Deep Learning"). There already is a sub-category of the ...

2

As per my knowledge, one of the recent papers on this topic can be found here, where the authors used machine learning algorithms to generate the optimal constellation shaping. Surprisingly, the results were in line with an old work: F. R. Kschischang and S. Pasupathy, "Optimal nonuniform signaling for Gaussian channels," in IEEE Transactions on Information ...

2

Some work has been done using auto encoder neural networks. The basic idea behind an auto encoder is that the neural network should "learn" (minimize a loss function) to output exactly what you input into it. This is what happens in communication systems: you want the receiver to output exactly what the transmitter sent. Check out this paper: https://arxiv....

2

Example with the following numbers (I use random numbers): There are 6 possible classes (face expressions in your case). You have 2000 examples (lets say 2000 photos of faces from which you know the correct face expression). There are 30 features. From each example you have extracted the 30 features and know the correct class. With these numbers, the input ...

1

Let's label your corners like this: 1-------2 | | 3-------4 For your destination. Let, $P_1, P_2, P_3, \text{ and } P_4$ be vectors representing the corners in pixel coordinates. For your source, Let $H$ and $W$ represent the height and width, and $(x,y)$ be a point in that rectangle you want to project. You can calculate your coefficients like ...

1

Well, yes and no. There are multiple factors, such as the level of annotation and the accuracy. If one requires human-level annotation performance on completely unknown scenes (with no prior information about context), and wants to annotate the images fully autonomously, without human intervention, then probably yes. Image annotation generally involves ...

Only top voted, non community-wiki answers of a minimum length are eligible