Image Categorization

Image Classification

Tagging images for image classification models and collecting data set meta data

Image Classification AI
Recognizing tiles with relevant objects with a ML Classifier
Image Classification AI
Categorizing the relevant images in the dataset

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Classification, Categorization, Data Cleaning for Machine Learning

How it Works

Tagging image-level tags allows to categorize images, use binary classifier and clean data. 
Challenges and solutions: 
*  Designing meta-data collection for project may include: descriptive value (comments),
binary categorization (good/bad image), and class categorization if images are properly cropped or consistent in zoom/size.
*  In the Geospatial applications, Image Classification works well for the standard formats such as tile service, allowing sizing up entire imagery data set  into standard slices, or tiles,  which are further classified with binary or class options. For example, does this tile include a building or not? 
Although, without a chance to define borders of the desired object, as it is done in the object detection machine learning models, pure classifiers may lead to difficulties in accuracy, and often get mis-interpreted.
At TaQadam, we used options of annotating data set in different pixel size images compiled of tiles to achieve accurate results. 

Tile map tagging

TaQadam: Making Visual Data AI-Ready

Image Annotation company with a complete solution on AI data training:
Image annotation tool, Data Management Platform and Trained Teams
  • Quality Assured Annotation
  • Managed Teams
  • Standard or Custom Data Output
  • Industry Specific Expertise
  • Platform for Data Management
  • Affordable or Value for Money
  • Security and Non-Disclosure
Learn more about our Company
If you are interested to request a Demo, or inquire regarding Image Annotation Pricing: