Questions tagged [datasets]

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

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A way to give more weight to particular data?

Let us for these purposes say with are working with any feed forward neural network. Let us also say, that we know beforehand that certain portion of our dataset arsignificantly more impactful or ...
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1answer
38 views

Why disentangling the features of variation in representation?

Consider the following excerpt from abstract of the research paper titled Better Mixing via Deep Representations by Yoshua Bengio et al. It has been hypothesized, ...
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1answer
33 views

How to handle an unbalanced dataset when training object detection algorithms?

I am training an object detection model, and I have some very highly unbalanced data annotations. I have almost 11,000 images, all with dimensions of 1024 $\times$ 1024. Within those images I have the ...
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2answers
37 views

Why data required for hyperparameter tuning is considered as an additional data?

Any parametric model may have parameters as well as hyperparameters. Learning algorithm deals with parameters and hyperparameters should be dealt outside learning algorithm. Consider the following ...
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1answer
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Data analysis before feeding to ML pipeline

I'm new to machine learning and I've been working through a dataset of ~3000 records with ~100 features. I've been hand rolling Python and R scripts to analyse the data. For example, plotting the ...
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1answer
25 views

An online editor that allows data labeling format

I have a set of students (~20) that will work on annotating data for an NLP project. The annotation task will be as in the following: ...
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1answer
34 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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2answers
189 views

What does it mean to have epochs=30 in Keras' fit method given certain data?

I have read a lot of information about several notions, like batch_size, epochs, iterations, but because of explanation was without numerical examples and I am not native speaker, I have some kind of ...
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1answer
229 views

Parameters to calculate affluence in localities of Metro city

I have to calculate the affluence in localities of Metro city. To calculate affluence, I am considering a parameter per capita income. Where I can get a dataset of it? What are other parameters I ...
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1answer
2k views

When training an object detection network for one class, should I include empty images in the dataset?

I fine tuned MobileNetSSD for object detection using a dataset with just one class (~4000 images). All the training images include at least one bounding box related to that class (no empty images). By ...
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1answer
397 views

Are standard deviation, variance, skew good features for ML?

Pretty simple question here: Is it useful to use the standard deviation, skew, kurtosis, or any other extrapolatory stats as features, and if so in which problem sets? In this case, I am talking ...
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22 views

Modelling of output neuron for mixed features?

Dataset in artificial intelligence, in general, consists of some features (say $n$). Assume that $m$ among them are output features. I want to model this function using neural network. So, input to my ...
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35 views

What are mathematically the factors of variation in deep learning?

The following paragraph from an answer tells us about factors of variation Factors of variation are some factors which determine varieties in observed data. If that factors change, the behaviour of ...
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32 views

What's the best way to feed stories to a neural network?

I'm trying to train a model that would generate stories. I have a dataset of 2000 stories prepared. They are tokenized and one-hot encoded. I can't load them all at once as a one big dataset, because ...
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18 views

Adding data to training results in loss random peaks

I have succesfully trained ssd_mobilenet_v2_keras for object detection, with a dataset of about 3700 images. Now I have more images to add. I tried adding only a few images (150-300) to see what ...
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Which Neural Network Topology to choose, are Transformers suitable?

I have a regression problem and I am not quite sure which architecture to choose. I never worked with transformers before, but I generally understand how they work and I think they might be suitable. ...
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Weight for Samples on SVM (Support Vector Machine)

There is a option sample_weight in fit(X[, y, sample_weight]) function (OneClassSVM, sklearn library). If I use the option ...
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1answer
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Comparing results of different image splicing methods on a part of the CASIA 2.0 dataset

So I am working on an image splicing detection algorithm using ResNet-50 model. I am using the CASIA 2.0 dataset which consists of 7491 Authentic images and 5123 Fake images. However out of the fake ...
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12 views

Simple example for side information

Many research papers contain the phrase "side information". After a search on side information, I got the following definition from here. In many problems of machine learning and computer ...
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12 views

Evaluation metric for time-series anomaly detection

My dataset is time-series sensor data and anomaly ratio is between 5% and 6% 1. For time-series anomaly detection evaluation, which one is better, precision/recall/F1 or ROC-AUC ? When empirically ...
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19 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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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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108 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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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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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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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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44 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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51 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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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
69 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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81 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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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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1answer
61 views

Is there a way of automatically drawing bounding boxes around interested objects?

Given thousands of images, where some of the images contain target objects and others do not, is there an easy way of drawing bounding boxes on these target objects rather than relying on manual ...
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19 views

Consecutive frames can be discarded when training an SSD/YOLO?

Let's say I have a number of videos, and I want to train an SSD/YOLO (or FRCNN) to detect objects. In the case of a large amount of videos, there will be a lot of frames extracted and transferred to ...
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40 views

Is there a RNN that can predict the next substitute in a floorball match?

Floorball is a type of floor hockey. During the game, substitutions can be made. The team is also allowed to change players any time in the game; usually, they change the whole team. Individual ...
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1answer
262 views

How many neurons would a network have after a training of 100k small images?

Is there any way to estimate how big the neural network would be after training session of 100,000 unlabeled images for unsupervised learning (like in STL-10 dataset: 96x96 pixels and color)? Not the ...

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