Questions tagged [datasets]

For questions related to sets of data and their use in AI.

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21 views

Identifying rotating and resizing letters with background noise

I'm trying to complete a certain type of captcha for academic purposes. Here is what it looks like: Between captchas the calligraphy of the letters is the same, but the letters may be resized and ...
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17 views

Image regression - estimating sensors from images

I am trying to use images to predict the sensor data of a racing game. Being a bit of a newcomer I have multiple questions. All help/suggestion is appreciated. Dataset The dataset looks something like:...
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10 views

Should we create a label mean group of small nearby objects in object detection?

I'm working on object detection models and my dataset sometimes has a lot of small objects (stay far from the scene) (overlapping and nearby) which is really annoying in annotating (it's too small and ...
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11 views

Split on dataset with some shared features?

I have a dataset with financial stock data, some of the features are shared, for example daily gold prices, while the stock price for each individual stock is different, the gold price would be the ...
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18 views

Pixel values of segmap in multi-class semantic segmentation

I'm preparing a dataset for a multiclass semantic segmentation using U-Net like architecture. To be precise, I've got it ready but a question came to my mind. How does pixel values of a segmentation ...
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1answer
32 views

Cnn for Combination of both digits and letters(small and capital) [closed]

Hi I am new to machine learning can anyone suggest open dataset consists of both digits and letters(small,capital) I want images consisisting of both digits and letters to train my cnn model and make ...
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21 views

Is it possible to do object detection on an object classification dataset?

I'm new to computer vision, which I find fascinating. I wonder whether it is possible or if there has been any research into going from object recognition data to object detection. In other words, ...
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53 views

How does pairwise comparison training work in XGBoost's XGBRanker?

I'm interested in learning to rank with pairwise comparison. While working on this, I found that XGBoost has a model called XGBRanker, which works very well. I want to find out how the XGBRanker ...
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4answers
58 views

How do I increase the size of an (almost) balanced dataset?

I am trying to add more data points in my (almost) balanced dataset for training my neural network. I have come across techniques such as SMOTE or Random Over Sampling, but they work best for ...
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1answer
34 views

How to source training data in ML for information security?

A company entrusts a Data Scientist with the mission of processing and valuing data for the research or treatment of events related to traces of computer attacks. I was wondering how would he get the ...
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10 views

Predicting training time using randomly generated datasets

Given a dataset, I need to predict the amount of time it will take to fit a model to it. I plan to do this by creating a csv containing the logs of previously fit models, and passing that data itself ...
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1answer
29 views

Can residual connections be beneficial when we have a small training dataset?

I have a classification problem, for which an inadequate amount of training data is available. Also, there is no known practical data augmentation approach for this problem (as no unlabelled data is ...
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15 views

Why doesn't U-Net work with images different from the dataset?

I have implemented a U-Net, similar to this implementation, but for a different dataset, this one, to segment roads. It works fine using the test folder images, but, for example, when I pick a print ...
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1answer
61 views

Why different images of the same person, under some restrictions, are in a 50 dimension manifold?

In this lecture (starting from 1:31:00) the professor says that the set of all images of a person lives in a low dimensional surface (compared the the set of all possible images). And he says that the ...
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18 views

Theoretical limits on correlation between classification algorithm performances

Are there any known theoretical bounds, or at least heuristic approaches, regarding the relation or correlation between the performances of any two different classification algorithms? For example, ...
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1answer
64 views

Would it be possible to determine the dataset a neural network was trained on?

Let's say we have a neural network that was trained with a dataset $D$ to solve some task. Would it be possible to "reverse-engineer" this neural network and get a vague idea of the dataset $...
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1answer
60 views

How to treat (label and process) edge case inputs in machine learning?

In every computer vision project, I struggle with labeling guidelines for border cases. Benchmark datasets don't have this problem, because they are 'cleaned', but in real life unsure cases often ...
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1answer
90 views

What dataset might Elon Musk's Dall-E have used?

Dall-E, it can generate many imaginative images from the description, even some peculiar images, how did they actually create this kind of dataset to train this AI , because there is not much of that ...
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49 views

In few-shot classification, should I use my custom dataset as the validation dataset and mini-ImageNet as the training dataset?

I am new to few-shot learning, and I wanted to get a hands-on understanding of it, using Reptile algorithm, applied to my custom dataset. My custom dataset has 30 categories, with 5 images per ...
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1answer
123 views

How should I generate datasets for a SARSA agent when the environment is not simple?

I am currently working on my master's thesis and going to apply Deep-SARSA as my DRL algorithm. The problem is that there is no datasets available and I guess that I should generate them somehow. ...
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39 views

Is training on single game each time appropriate for an agent to learn to play checkers

I was facing a problem I mentioned in a previous question but after a while, I realize that maybe the problem in the dataset not in the learning rate. I build the dataset from white positions only i.e ...
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19 views

Where can a dataset of relationship between images be used?

I'm making a platform that will collect data about the relationship between different images. For example, if I have three images: a Christmas tree, a gift and Santa... then these will be connected by ...
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13 views

Is there a pre-trained network trained on RGB-D (4) channels? [closed]

The most used pre-trained networks for computer vision (e.g. ResNet50) are trained on 3 channels (RGB). At the same time, many cameras used in robotics return RGB-D outputs, that is including depth ...
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2answers
30 views

Why can't we combine both training and validation data, given that both types of data are used for developing the model?

Sorry if I sound confused. I read that data to be fed to a machine are divided into training, validation and test data. Both training and validation data are used for developing the model. Test data ...
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1answer
82 views

Can we use ML to do anything else other than predicting (in the case of mathematical problems)?

(The math problem here just serves as an example, my question is on this type of problems in general). Given two Schur polynomials, $s_\mu$, $s_\nu$, we know that we can decompose their product into a ...
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37 views

Is there any rule of thumb to determine the amount of data needed to train a CNN

I am training an AlexNet Convolutional Neural Network to classify images in a dataset. I want to know if there is any general rule for using data augmentation in training a neural network. How can I ...
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1answer
69 views

How robust are deep networks to class imbalance?

Before deep learning, I worked with machine learning problems where the data had a large class imbalance (30:1 or worse ratios). At that time, all the classifiers struggled, even after under-sampling ...
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50 views

What could be a good $\mathcal{R}$ dataset in the article “Old Photo Restoration via Deep Latent Space Translation”?

There are three domains in this article: Old Photo Restoration via Deep Latent Space Translation. The real old pictures noted by $\mathcal{R}$, the artificial old pictures noted by $\mathcal{X}$, and ...
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1answer
72 views

Is it okay to think of any dataset in artificial intelligence as a mathematical set?

A dataset is a collection of data points. It is known that the data points in the dataset can repeat. And the repetition does matter for building AI models. So, why does the word dataset contain the ...
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1answer
168 views

Should we also shuffle the test dataset when training with SGD?

When training machine learning models (e.g. neural networks) with stochastic gradient descent, it is common practice to (uniformly) shuffle the training data into batches/sets of different samples ...
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1answer
59 views

What is the reason for taking tuples as vectors rather than points?

Across the literature of artificial intelligence, especially machine learning, it is normal to treat the tuples of datasets as vectors. Although there is a convention to treat them as data points. ...
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34 views

Transforming neural network target values before training

Consider the scenario in which I am measuring certain $f(a,x)$, which i want to be the target value for some related input $g(a,x)$. In other words, I am trying to map $$g(a,x)\Rightarrow f(a,x)$$ I ...
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1answer
61 views

Is it possible to know the distance objects are from camera based on only knowing one object's height?

I am doing a project where I have to know distance a particular object is from camera. In the photo I only know one of the object's height, but I don't know how far away that object is and I don't ...
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29 views

How to find distance between 2 points when dimensions are all of different nature?

I have a dataset with four features: the x coordinate the y coordinate the velocity magnitude angle Now, I want to measure the distance between two points in the dataset, taking into account the ...
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75 views

Multi-label dataloading bottleneck Pytorch

I am trying to write custom dataset and dataloader for pascal-voc-2007. It is a multi-label classification problem. There is csv file to hold the name of the images and their corresponding labels. I ...
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69 views

Which loss function to choose for imbalanced datasets?

For imbalanced datasets (either in the context of computer vision or NLP), from what I learned, it is good to use a weighted log loss. However, in competitions, the people who are in top positions are ...
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1answer
70 views

What are some examples of functions that machine learning models compute?

My simple understanding of AI is that it is based on a mathematical model of a problem. If I understood correctly, the model is a polynomial equation and its weights are calculated by training the ...
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1answer
23 views

Can a neural network be trained on a dataset containing only values for true output for a classification problem?

I am using a dataset from Google which contains 1,27,000 data points on simulated concentrations of the atmosphere of exoplanets which can sustain life. So, the output label of all these data points ...
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42 views

Could the neural network automatically calculate and get different one-to-many quantities relative to their parent quantity?

Let's say I have a primary dataset that its secondary dataset is hundreds to match and group like an one-to-many relationship. I'm new in this world of the AI but my problem is that many child groups ...
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2answers
113 views

Can we use genetic algorithms to evolve datasets?

Genetic algorithms are used to solve many optimization tasks. If I have a dataset, can I evolve it with a genetic algorithm to create an evolved version of the same dataset? We could consider each ...
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1answer
49 views

How can I classify houses given a dataset of houses with descriptions?

I have a dataset with a number of houses, for each house, I have a description. For example "The house is luxuriously renovated" or "The house is nicely renovated". My aim is to ...
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34 views

Can I use the full dataset for training the CNN feature extractor?

I built a CNN model for extracting features from its dense layer. The extracted features are then used for classification using KNN and Random Forest classifier. My question is, can I use the whole ...
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9 views

Quality of synthetic sample and corresponding label generated by SMOTE or ADASYN?

When SMOTE or ADASYN create synthetic sample and the corresponding label, is the quality of the label trust worthy OR should I should double check the label by myself ? Particularly in a ...
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31 views

How should I label images to get high accuracy with YOLO?

I am new to Object Detection with Yolo and I have questions regarding the labeling (for custom objects): Is there any guideline or tips on how to label images to have high accuracy at the end? ...
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0answers
19 views

Conditional GAN on harder datasets

I have seen conditional GANs often applied to easier datasets like MNIST and CIFAR-10 to reasonable success, but at the same time these datasets are simple enough that naïve CNNs can fairly easily max ...
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0answers
35 views

Can I train an object detection model with images with a white background?

To be more specific I have a dataset of 2400 images with unbalanced classes, 1 object per image and sometimes some objects are repeated along the dataset but in a different position and rotation of ...
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1answer
496 views

How to generate labels for self-supervised training?

I've been reading a lot lately about self-supervised learning and I didn't understand very well how to generate the desired label for a given image. Let's say that I have an image classification task, ...
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0answers
137 views

Multilabel stratified split for images/object detection

I am working on an object detection model and have thought of looking into stratified splits for the dataset. Now since I am doing object detection I have a variable number of "labels" for ...
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2answers
79 views

How can I predict the true label for data with incomplete features based on the trained model with data with more features?

Suppose I have a model that was trained with a dataset that contains the features (f1, f2, f3, f4, f5, f6). However, my test dataset does not contain all features ...
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53 views

Can I train a neural network with multiple datasets (e.g. 25)?

I want to create a neural network that I can train with many datasets (e.g. 20 - 25 datasets). Can I use transfer learning for this? Or is there a better approach than this?

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