Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

Questions tagged [model-request]

Use this tag when you're looking for machine learning models that could be used to solve your specific problem.

62 questions
10
votes
2 answers

Is there any existing attempt to create a deep learning model which extracts vector paths from bitmaps?

I need an algorithm to trace simple bitmaps, which only contain paths with a given stroke width. Is there any existing attempt to create a deep learning model which extracts vector paths from bitmaps? It is obviously very easy to generate bitmaps…
arthur.sw
  • 151
  • 1
  • 8
9
votes
2 answers

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

I am trying to detect a TV channel logo inside a video file. So, simply, given an input .mp4 video, detect if it has that logo present in a specific frame, say the first frame, or not. Here's the first example of a frame with a logo. Here's the…
Tina J
  • 973
  • 6
  • 13
8
votes
2 answers

Apart from Reinforcement Learning, are there any other machine learning approaches to play video games?

OpenAI's Universe utilizes RL algorithms. I also know that Q-learning has been used to solve some games. Are there any other ML approaches to solve games? For example, could we use genetic algorithms to develop agents that solve games?
U754V
  • 83
  • 5
7
votes
3 answers

What are some information processing models besides MLPs?

Feedforward or multilayered neural networks, like the one in the image above, are usually characterized by the fact that all weighted connections can be represented as a continuous real number. Furthermore, each node in a layer is connected to…
user289661
  • 419
  • 3
  • 11
5
votes
1 answer

Which machine learning approach should I use to estimate how many products a research group should have to improve its category?

Currently, in my country, there is a system in which certain groups of researchers upload information on products of scientific interest, such as research articles, books, patents, software, among others. Depending on the number of products, the…
LP0
  • 83
  • 4
5
votes
1 answer

Which neural network can count the number of objects in an image?

I'm looking for a neural network architecture that excels 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 crowd counting. I'm looking for articles about…
ron653
  • 83
  • 1
  • 8
4
votes
3 answers

Which neural network to use for optical mark recognition?

I've created a neural net using the ConvNetSharp library which has 3 fully connected hidden layers. The first having 35 neurons and the other two having 25 neurons each, each layer with a ReLU layer as the activation function layer. I'm using this…
Hamza Abdullah
  • 43
  • 5
4
votes
0 answers

Can AlexNet be changed to produce floating-point outputs in the range $[-1, 1]$, and, if not, which model should I use?

I'm developing a game AI, which tries to master racing simulation. I already trained a CNN (AlexNet) on in-game footage of me playing the game and the pressed keys as the target. I had two main issues with this setup: Extracting the current speed…
TheJD
  • 103
  • 5
4
votes
2 answers

What algorithms are used in Artificial General Intelligence research?

I've read on wiki that already in 2017 there were over 40 institutions researching AGI, and I wonder what type of algorithms are being studied and developed in this field. For example, for comparison with narrow AI, where models/techniques, such as…
GKozinski
  • 1,240
  • 8
  • 19
4
votes
2 answers

Which neural network can I use to solve this constrained optimisation problem?

Let $\mathcal{S}$ be the training data set, where each input $u^i \in \mathcal{S}$ has $d$ features. I want to design an ANN so that the cost function below is minimized (the sum of the square of pairwise differences between model outputs) and the…
user3489173
  • 179
  • 6
4
votes
0 answers

What are some neural network models that can use auxiliary info during training for image segmentation?

What are some deep learning models that can use supplementary information other than RGB channels for image segmentation? For example, imagine a poorly shot image of a river (blue) that shows a gap, and the supplementary information is detailed…
Nanako Honda
  • 41
  • 1
3
votes
0 answers

Is there a general adversarial network that can take multiple low quality images to create a higher quality image?

Is there a general adversarial network that can take multiple low-quality images of a subject to create a higher quality image of the subject? SRGAN just takes a single low res image and makes it high res but I need something that can take multiple…
Forth Temple
  • 59
  • 1
3
votes
1 answer

What would be the most simple approach to solve crossword puzzles?

I have to model an AI that should be able to understand clues and find the answer from a specified word database. I came across several papers that solve the problem with training neural networks or processing the clues by training several machine…
Mehmet
  • 41
  • 1
3
votes
2 answers

Which model should I use to find (only) the object location (in terms of coordinates) in an image?

I am generating images that consist of points, where the object's location is where the most overlap of points occurs. In this example, the object location is $(25, 51)$. I am trying to train a model to just finds the location, so I don't care…
scooter
  • 31
  • 3
2
votes
2 answers

Which neural network should I use to approximate a specific but unknown function?

We have convolutional neural networks and recurrent neural networks for analyzing, respectively, images and sequential data. Now, suppose I want to approximate the unknown function $f(x,y) = \sin(2\pi x)\sin(2\pi y)$, with domain $\Omega =…
timudk
  • 31
  • 2
1
2 3 4 5