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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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
39 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
22 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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0answers
35 views

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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0answers
24 views

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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0answers
20 views

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 ...
5
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1answer
67 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
144 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 ...
2
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1answer
323 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
1k 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
601 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 ...