Questions tagged [data-labelling]

For questions related to the problem of labelling data and data labelling techniques in the context of artificial intelligence.

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Can I perform 3D point cloud per-point labeling from binary classification alone?

All, It seems that the process of individually labeling points in 3D point clouds is no small task. I believe that's why tools like these exist: Sagemaker Pointly But ... what if there are only two ...
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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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How to label images for image segmentation (with TensorFlow)?

I am following this tutorial on image segmentation on the TensorFlow website. The website uses its own labeled images for the tutorial, so the images have data that says which pixels are a part of the ...
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Is soft labeling the same thing as label smoothing?

I have some data with soft labels and I am trying to figure out the best approach to solve the problem with Machine Learning (since regular classification is of the table, i.e. hard labels). However, ...
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1answer
27 views

An online editor that allows data labeling format [closed]

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
196 views

How to add negative samples for object detection?

My question is: how to add certain negative samples to the training dataset to suppress those samples that are recognized as the object. For example, if I want to train a car detector. All my training ...
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How to deal with images that do not contain any object of interest?

I'm currently working on an iOS App where I want to detect if there is a table, chair or bench in the current camera input. My idea was to take the MobileNetV2 model and get it to classify these three ...
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2answers
98 views

What is the difference between "ground truth" and "ground-truth labels"?

I'm aware that the ground-truth of the example at the top left-hand corner of the image below is "zero" However, I am confused about the meaning of the terms ground truth and ground-truth ...
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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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1answer
41 views

Is intersection of labels acceptable in computer vision?

I have a dataset, where objects are very close to each other. So, the question is: what is the best approach to label them? There are two possible options: mark objects so that they will not ...
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1answer
24 views

Is there a methodology for splitting up annotated orthophotos into smaller photos that retain the original bounding boxes?

I'm trying to train an object detection algorithm (i.e. YOLOv4 Scaled, Faster R-CNN) on data taken from large orthophotos. Let's say I have one class, and I label the entire orthophoto with bounding ...
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Data Augmentation of store images using handwritten labels

I am new to AI and NN. I've started learning using Geron's book on Tensorflow. My first project ("Smart Shelf") is to determine which items in a store have been purchased and need refilled. ...
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How would one modify the Mask-RCNN head for polyline detection?

In Mask-RCNN they modify the standard mask head for human pose keypoint detection with the following tweaks: Each keypoint is a 1-hot mask Instead of sigmoid non-linearity on the output of the final ...
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For binary classification learning problems, how should I label instances where I'm only 60% sure?

I've come across a few binary classification problems lately where the labelling was challenging even for an expert. I'm wondering what I should do with this. Here are some of my suggestions to get ...
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1answer
70 views

Do models train better if the labelling information is more specific (or dense)?

I'm working on a project where there is a limited dataset of videos (about 200). We want to train a model that can detect a single class in the videos. That class can be of multiple different types of ...
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1answer
158 views

How to deal with a small amount of labeled samples?

I'm trying to develop skills to deal with very small amounts of labeled samples (250 labeled/20000 total, 200 features) by practicing on Kaggle "Don't Overfit" dataset (Traget_Practice have ...
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1answer
340 views

How to detect multiple playing cards of the same class with a neural network?

I want to train an AI to detect the class (i.e. suit and rank) of playing cards. Playing cards from different decks may use slightly different shapes or colors to represent these attributes, and I ...
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1answer
2k views

How to label edited images after data augmentation?

I am new to neural networks, I've only started studying and learning about the subject a year ago, and I just started building my first neural network. The project is a little bit ambitious: A browser ...
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2answers
646 views

What is the effect of mislabeled training data?

Collecting and labeling training data for supervised learning tasks is incredibly time-consuming and costly. For instance, let's say you wrote a script that went on Google images and got you 5000 ...