When and Why Companies Choose Data Creation

May 17, 2022

Computer vision based AI models are required to interpret and operate within a complex world, filled with difference and variety. As a result machine learning algorithms need to be trained with image and video data that reflects a chaotic real world. Image and video datasets for machine learning need to be collected and organised before the annotation process can begin.

And this is often where issues with data quality and usefulness can begin to manifest. Collecting the volume of image or video data that today’s computer vision projects need is a significant challenge, one that can overwhelm large and small companies alike, leading many to outsource data collection. However, even outsourcing to experts can result in datasets that are not suitable for specific purposes.

This is where data creation comes in. Professional annotation providers, like Keymakr, are creating images and videos that can meet the demands of AI innovators. This blog will look in detail at the difficulties of data collection and show how data creation, carried out by experts, might provide solutions.

The challenges of data collection

Data collection is the primary means by which training datasets are created. Data can be collected from large open source databases, or it can be collected manually by organisations, using web scraping tools. This represents a significant investment of time and resources for companies which is why many turn to data collection services.

Data collection
Data collection | Keymakr

However, even expertly collected datasets can still have significant drawbacks:

  • Quality: Raw image and video data can feature artefacts and oddities as a result of human error. Poor framing of objects could result in unusable training data outputs.
  • Density: Images may not feature a large enough number of objects. Under populated training images may result in poorly performing systems.
  • Variance: Dataset images and video may not contain a varied collection of objects that might be of relevance to a computer vision model.
  • Legal concerns: Data scraped from the internet may be problematic in terms of intellectual property rights or data protection. Companies may not have the experience to navigate these complex issues.

The advantages of bespoke data creation

As shown above data collection can result in images and videos that do not meet the needs of a growing machine learning model. This is when companies turn to data creation, to get the specific material that they need. Bespoke datasets can maintain high quality because they are created specifically for AI training.

Data creation
Data creation | Keymakr

Data creation can also add much needed variety and density to datasets, allowing developing models to overcome bias. Edge cases that might confound computer vision models can be created and inserted into training data, allowing it to reflect the full complexity of the real world.  

The essentials of data set creation

Data creation provides essential depth, variety, quality for machine learning training data. However, for many companies, producing images and video in house is practically impossible. Outsourcing to annotation services is often the best way to access bespoke images and video. The advantages of outsourcing this work include:

  • Experience: Annotation experts have a wealth of experience when it comes to recognising the kinds of data that companies need.
  • Equipment: Annotation services are able work with specialised equipment for image and video creation. This includes cameras, sound equipment, and studio spaces.
  • Background creation: Annotation services can often construct or access sets in which images and video can be shot. This allows for the creation of data featuring environments that might be hard to find in public sources.
  • Legal compliance: Outsourcing data creation can ensure that images and video are created according to privacy regulations and in line with best legal practices.
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Data creation experts

Often the only way to get the right training data for machine learning is to make it yourself. Keymakr has the expertise and experience to create bespoke datasets and annotate them to the highest levels of accuracy.
Contact a team member to book your personalized demo today.

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