Questions tagged [model-request]

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

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Is there any work done on topic agnostic binary topic classification?

In the recent preprint paper Tree-based Focused Web Crawling with Reinforcement Learning a new model is introduced to classify web pages called KwBiLSTM. The input to this model is a featurized ...
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Machine Learning Model to assess risk level of individuals of concerns (criminals) and risk level of different public saftey stations

I am working in an academic project where I want to develop ML model to assess different aspects of public safety. I want to narrow down these aspects to 2 items: 1- risk level of individuals of ...
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1 answer
37 views

Image classifier model which predicts objects and it's relevant areas with a combination of words

I have experience with image classification models such as CNN and Vision Transformers but this time I want to try a new thing (For me). First please check the below image to understand what I want ...
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24 views

How is it possible to detect anomalies in batches of 2 minutes of web access logs?

I have data coming from web access logs in the following form: ...
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1 vote
1 answer
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Can the output layer be connected to multiple layers?

Normaly, the output layer is only connected to the second last layer. Is there any model that the output layer is connected to multiple layers (For example, the second last layer AND the layer before ...
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1 vote
1 answer
40 views

Make an NN utilize other NNs as part of its decision process

Suppose I have a NN that learns to predict the time it takes a robot to move between two jobs. That's three inputs (for starters): robot, job A, job B. Not all robots travel at the same speed, and ...
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2 votes
1 answer
91 views

How can I generalize a machine learning model to multiple curves?

I have a family of convergence curves as you can see in the image below: I would like to train a model that fits reasonably well to all the curves at the same time in my dataset. Is it possible? Do ...
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14 views

How to model a set-to-set mapping with graph neural networks?

I have a task on a heterogeneous graph where a set of nodes is given as input and some of the nodes are acceptable outputs. The dataset essentially consists of pairs (X, Y) where X is a set of nodes ...
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Which existing model could be used for wind speed and direction prediction?

I am trying to predict the wind speed and wind direction in a graph network for a geographical area. The dataset includes the start and end nodes, the distance between them, and wind speed and ...
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1 vote
1 answer
85 views

ML model to predict timeouts

I am new to ML and am trying to build a model to predict timeouts for a website. The website is being monitored once a minute and the data consists of a timestamp and the response time in seconds. E.g....
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12 views

Which ML algorithm/model should I use to learn temporal dependencies between binary variables?

Let's consider the following setting: We have 1000 binary variables (X1 ... X1000). At each time step each of the variable can either switch (1 to 0 or 0 to 1) or stay the same. I am looking for a ...
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12 views

How to approach in panel data using machine learning?

I have monthly electricity consumption data for the last year of 100k households. So there is a total (100k*12)= 1.2 million data points. I am willing to use this dataset to predict the individual's ...
2 votes
1 answer
74 views

How might AI analyze abusive discussion using natural language grammar?

Opening thoughts This does not only apply to SE comments, but the idea in general. This is not a Question for Linguistics.SE; those Questions might come later, after AI analysis. Example Linguistics ...
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1 answer
105 views

Which approach can I use to generate forged signatures from real ones?

I am in internship period and I'm working on a signature verification problem. This process needs real and forged signatures. All I have are the real signatures (like 30 signatures per person), and I ...
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30 views

3D object dimensions calculation from RGB camera

I happen to have one project which consists of a camera that should read barcode and calculate the parcel's dimensions. Barcode information is used for determining the parcel's designated address, etc,...
1 vote
1 answer
1k views

Are there some known neural networks that, given an input image, can generate a similar image, with the same topic?

Are there some known neural networks that, given an input image, can generate a similar image, with the same topic? Example: input = a photo of a cat on a green table, output = a generated photo of ...
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0 votes
1 answer
61 views

Is there an approach where the output of one neural network is used to choose the next neural network?

I'd like to design a deep learning architecture in which the output of a primary neural network $M_{\theta}$ determines which neural network $N^i_{\alpha}$ in a set of secondary networks $\mathcal{N}$ ...
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80 views

Is it effective to use deep learning method to produce a 1D signal as output from a 2D image as input?

I have a 1D signal that will produce a 2D image after some image processing algorithm. Would it be possible and effective to use deep learning method to reproduce the 1D signal if I have the 2D image ...
1 vote
1 answer
145 views

How to train an ML model to convert the given lyrics into a song by a particular singer?

I am interested in training a machine algorithm to convert the lyrics I give into a song by a particular singer. My language is non-English (south Indian) The songs are mostly monophonic (very few ...
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2 votes
0 answers
65 views

Non-face "deepfakes" in videos

Instead of changing faces (like James Bond to Putin) what if, given sufficient training data, I wanted to: Remove or add some windows from a brick house? Convert a glass of red wine to a glass of ...
1 vote
0 answers
13 views

What is the best way to train a text-based regressor model?

I want to build a deep learning model that can predict a continuous value (LogP in this case) given text inputs (SMILES notations in this case), the dataset is as illustrated below. SMILES notations ...
1 vote
0 answers
148 views

What is the fastest multi-human pose estimation model?

I am trying to find an accurate and fast multi-person human pose estimation that I can train on with custom data. I have been searching for a little while and I may not be up-to-date on the newest ...
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2 votes
1 answer
36 views

What type of neural network do you need if you want to detect an action or dynamic pattern instead of a static pattern?

Let's say that you want to detect if a man is running, walking, or dancing instead of just detecting a man still. What type of neural networks will you use for this purpose?
4 votes
2 answers
196 views

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 ...
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1 vote
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75 views

What is the best way to train neural network with imbalanced mixed data (images and structured data)?

I have structured data and image data to solve a regression problem. One sample of structured data can be related to N images. If I use only structured data, I get decent performance, but not enough ...
2 votes
0 answers
21 views

Model for direct audio-to-audio speech re-encoding

There are many resources available for text-to-audio (or vice versa) synthesis, for example Google's 'Wavenet'. These tools do not allow the finer degree of control that may be required regarding the ...
0 votes
1 answer
107 views

What type of ANN architecture to choose?

I have $N$ number of teachers each of which has an input feature vector ($25$ dimensional) consisting of positive numerical values for different quality of aspects (for example: lecturing ability, ...
4 votes
1 answer
148 views

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 ...
1 vote
1 answer
54 views

What kind of neural network should I build to classify each instance of a time series sequence?

Let's say I have the time-series dataset below-left. I would like to train a model in such a way that, if I feed the model with an input like the test sequence below, it should be able to classify ...
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1 vote
1 answer
46 views

What would be the state of the art image captioning deep learning model?

I saw a couple of architectures, like CNN-LSTM, with and without attention model, use of Glove vector, self-critical models, etc. I am overwhelmed looking at different notebooks and architectures, ...
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26 views

Can RNNs be used to classify these time series into two classes?

My task is to classify into two classes the time series like these shown in the figure. The figure shows one class on the left sub-figure and second one on the right. The series are shown in pairs ...
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0 votes
2 answers
69 views

Should I use U-net to label keys in a keyboard image?

This is a 600*800 image. Which algorithm/model should I use to get an image like the one below, in which each key is detected and labeled by a rectangle? I guess this is some kind of a segmentation ...
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1 vote
1 answer
85 views

Which approach should I use to classify points above and below a sine function $y(x) = A + B \sin(Cx)$?

In a linear regression problem, a line can divide a data set into two categories. So, basically, points above the line belong to category 1, and points below the ...
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1 vote
0 answers
62 views

Setting up a deep learning architecture for multi-dimensional data

The input data is thousands, millions of 4x1000 matrices. Each row consists of 3 small natural numbers (1000 combinations) and a corresponding real number between 0 and 1. The output is a 1x1000 ...
1 vote
1 answer
61 views

Is it possible to make a neural network to solve this "reaction time test"?

I'm thinking about writing an essay on the comparison between the human nervous system (reaction time) and a neural network that does the same reaction time test. I am very new in this area, so I was ...
1 vote
1 answer
159 views

Is there a graph neural network algorithm that can deal with a different number of input and output nodes?

I am new to graph neural networks and their applications. I have an input graph $G = \{V, E\}$ and an output graph $G' = \{V', E'\}$ where the number of nodes $V$ and $V'$ are different. I am trying ...
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1 vote
0 answers
128 views

Object detection approaches without anchors and NMS

The Context From all of the problems I have worked with in computer vision, the most challenging one is the object detection. This is not because the problem itself is complex to understand or bad ...
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2 votes
1 answer
144 views

Which neural network can approximate the function $y = x^2 + b$?

I am new to ANN. I am trying out several 'simple' algorithms to see what ANN can (or cannot) be used for and how. I played around with Conv2d once and had it recognize images successfully. Now I am ...
2 votes
1 answer
66 views

How many ways are there to perform image segmentation?

I'm new in Artificial Intelligence and I want to do image segmentation. Searching I have found these ways Digital image processing (I have read it in this book: Digital Image Processing, 4th edition)...
9 votes
1 answer
2k views

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? ...
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0 votes
1 answer
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Neural networks for sports betting

I want to design a neural network that can be used for predicting sports scores for betting, specifically for American football. What I’d like to do is create a kind of profile for each game based on ...
2 votes
0 answers
207 views

Is there a neural network that can output a unit vector that is parallel to the input vector?

I'm wondering if there is a NN that can achieve the following task: Output a unit vector that is parallel to the input vector. i.e., input a vector $\mathbf{v}\in\mathbb{R}^d$, output $\mathbf{v}/\|\...
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4 votes
0 answers
49 views

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, ...
1 vote
1 answer
43 views

Is any classifier not subject (or less susceptible) to fooling?

Is any classifier not subject to fooling as in here? My question is related to this, but not an exact duplicate. What I wanted to ask is that any classifiers inherently do not subject (or less prone) ...
3 votes
1 answer
3k views

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 ...
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2 votes
1 answer
118 views

Is there any research on models that make predictions by also taking into account the previous predictions?

With the recent revelation of severe limitations in some AI domains, such as self-driving cars, I notice that neural networks behave with the same sort of errors as in simpler models, i.e. they may be ...
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3 votes
2 answers
2k views

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 ...
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2 votes
2 answers
604 views

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 ...
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4 votes
3 answers
1k views

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 ...
5 votes
1 answer
205 views

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 ...
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