# 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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### Is there an argument against using the (reviewed) predictions of a model as ground truth to further train exactly this model?

I plan to use my predictions as ground truth to continue training my model. These predictions are of course reviewed during this process. Is there an argument against that (reinforcement of slight ...
• 73
12 views

### Which rule could I use to identify suppliers who are likely to leave us or stay with us?

I have 3 domains of supplier data (Jan 2017 to Jan 2022) and they are as follows Purchase data - Contains all the purchase (of product) data made by the suppliers with us. It contains columns such ...
• 101
22 views

### When generating segmentation mask, is it better for the ground truth mask to be a bit inside the object than outside?

I got asked this question today, and I was wondering. When manually annotating images for ground truth, is it better for the model to get segmentation masks that are a bit inside the object or a bit ...
• 101
70 views

### Is there a standard term for the following flaw in the data?

I wonder if following characteristic of data has some standard "professional" or scientific term associated with it. Let's assume that I have a set of dog/cat images labeled 0 for a cat and ...
• 1,039
39 views

### What techniques exist to increase the learning importance of difficult-to-learn labels over easy ones?

I am training a model to place labels in image data. Some labels are learnt very quickly by the model while others take a long time to perfect. I cannot simply add more labeled data with only the ...
28 views

### What are the "per image" annotations that are generally used for image datasets in AI?

Computer vision is highly benefited by AI algorithms. Image data is abundantly available. There are different varieties of tasks such as image classification, prediction, segmentation, generation, ...
• 3,099
1 vote
46 views

### General approaches in text encoding and labelling for NLP [closed]

What are the approaches of encoding text data? I would be glad to hear some summarization from experienced persons. And are there any solutions accepting words outside the vocabulary and including ...
• 111
67 views

### Best practice for handling letterboxed images for non fully-convolutional deep learning networks?

I'm working on a depth estimation network. It has two outputs: A relative depth map A scalar for scaling the relative depth map into an absolute depth map. This second output uses dense layers so ...
• 153
54 views

### How to label unsupervised data for deep learning multi-classification

I have unlabeled credit card transaction data that has the following columns: ...
36 views

### Should I train my network for classification on samples whose ground truth label is ambiguous?

Imagine that I am training a model to classify handwritten digits. Suppose there are some bad quality images that could be classified by a human as either 0 or 8, 1 or 7 or other commonly ...
• 201
40 views

### 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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72 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 ...
• 119
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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, ...
30 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: ...
• 123
938 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 ...
• 123
1 vote
36 views

### 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 ...
• 11
1 vote
998 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 ...
• 201
55 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 ...
38 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 ...
• 119
45 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. ...
24 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 ...
• 1,109
74 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 ...
• 153
201 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 ...
• 181
426 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 ...
• 121
1 vote
436 views

### How do I change the annotations of variable-size images after having resized the images to a fixed size?

In the data-sets like coco-text and total-text, the images are of different sizes (height*width). I'm using these data sets for text detection. I want to create a DNN model for this. So the input data ...
87 views

### How can computers beat humans at image recognition, if humans may incorrectly label the images?

For supervised learning, humans have to label the images computers use to train in the first place, so the computers will probably get wrong the images that humans get wrong. If so can computers beat ...
• 181
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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