Answers.Body: <p>Yes this is certainly possible...</p>
  <p>What you want to do is apply a weight to particular classes by proportion of the imbalance(assuming nothing else related to the problem is of note).</p>
  <p>See this <a href="https://stackoverflow.com/questions/60253082/weighting-samples-in-multiclass-image-segmentation-using-keras">post</a> for details</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-07-01T05:52:37.040Z
Answers.LastActivityDate: 2022-07-01T05:52:37.040Z
Answers.UserDisplayName: hisairnessag3
Body: <p>Image imbalance is one of the major factor in the performance of DL model. Some of the methods that I found to tackle this are oversampling, under-sampling, SMOTE. Over-sampling has cons as it makes model to be overfit.undersampling results in loss of useful information.Again using SMOTE technique also won't works well on image datasets(as per web references).</p>
  <p>What is the right way to handle imbalance in image datasets (multi-class problem)?</p>
  
Tags: <deep-learning><image-processing><data-science><imbalanced-datasets>
Title: What are the possible ways to handle imbalance in multi-class image datasets?
UserDisplayName: Dilip C M Dept of MCA
ThreadText: # What are the possible ways to handle imbalance in multi-class image datasets?
  
  (Asked by: username_0 on 2022-06-30)
  
  Image imbalance is one of the major factor in the performance of DL model. Some of the methods that I found to tackle this are oversampling, under-sampling, SMOTE. Over-sampling has cons as it makes model to be overfit.undersampling results in loss of useful information.Again using SMOTE technique also won't works well on image datasets(as per web references).
  
  What is the right way to handle imbalance in image datasets (multi-class problem)?
  
  **Tags:** deep-learning, image-processing, data-science, imbalanced-datasets
  
  
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  ## 1 answers
  
  ### Answer by username_1 on 2022-07-01. Score: 1
  
  Yes this is certainly possible...
  
  What you want to do is apply a weight to particular classes by proportion of the imbalance(assuming nothing else related to the problem is of note).
  
  See this [post](https://stackoverflow.com/questions/60253082/weighting-samples-in-multiclass-image-segmentation-using-keras) for details
  
  
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