What You Need To Know About Data Creation: Data Annotation, Labeling, Segmentation, And More!

Artificial intelligence is, at its core, bound by the data that is used to create it. This is where AI data annotation companies like Keymakr come in. Our job is to make custom data sets that directly impact your project, which leads to customized AI solutions. However, with the seemingly infinite growth of data in our world, it is becoming more difficult to know what data will help develop the solutions that you need. So, of course, collecting data is the first step. It then needs to be organized and structured for your particular problem. Otherwise, too general of an answer will be generated.

Data Labeling: What Is It And Why Is It So Crucial

An estimated 85-90% of the vast amounts of data produced today are unstructured. If this undefined data were fed into an AI system, it would essentially be trying to identify objects, for example, with a blindfold on. It knows the objects are there but will have a harder time identifying and classifying objects or looking for patterns. Even something as simple as labeling whether data is text, video, audio, or an image can narrow the datasets and provide a more specific model.

Segmentation: The Difference between Video, Image, and Semantic Segmentation

Generally speaking, we can fit segmentation under these three umbrella terms. Segmentation work can get much more specified, but the core process of each of these still applies. Each of these divisions helps AI understand what objects make up a video, image, or text line and labels them to track patterns. This is a crucial part of AI learning, providing context and understanding to a dataset for the AI to process.

• Image annotation is going through an image and identifying what is in it. The classifications can be general or extremely specific, but the goal is to identify aspects of an image for the AI to recognize moving forward. This image classification can be used to identify an apple vs. an orange, for example, or can be used in the medical field to classify x-ray imaging.
• Video annotation is similar to image annotation. We take a video and break it down frame by frame to identify and track objects throughout a video. Autonomous driving data collection is a common example, identifying the double yellow line in each frame's middle of the road. Another example of object recognition would be license plate identification, where the AI would look when tracking the forward-facing camera to identify a license plate on the car ahead of them.
• Semantic segmentation is the identification of patterns and context within a text file. Creating a semantic segmentation dataset is extremely important when it comes to machine learning. For example, the differences in vernacular between different parts of the U.S.A is huge, or even the compiling of technical jargon for certain types of industries is a huge task but crucial for AI learning. The depth of human language is staggering, and providing AI with accurate datasets for particular problems will be the difference between general or specific solutions.

Data Collection vs. Data Creation

Keymakr is at the forefront of AI learning services thanks to its creativity and experience working on unique projects. The more unique the project, the harder it will be to potentially find good data for the AI to process. This is where data creation comes into play.

Data creation is tailor-made for your specific project. This can involve a wide variety of production processes and strategies. One example Keymakr has used is “warehousing”. Hundreds of hours of video and images were shot to track warehouse workers’ movement. This was then labeled and annotated so cameras would recognize dangerous situations if a worker had fallen or was trapped behind something, making the workplace safer.

Data collection is an equally massive task. The amount of data available is constantly growing, and sorting through it for data that will yield the best results is difficult. Keymakr has proprietary tools that have been developed to collect data for any particular project faster and more efficiently than ever before. Here are some of the fields in which we have done cutting-edge work:

• Retail
• Food Industry
• Face Recognition
• Weather prediction
• Medical Imaging

Artificial intelligence data annotation is the most crucial part of any project that wants to take advantage of the vast amounts of data available in the world. Identifying and sorting that data is where companies like Keymakr come in. Outsourcing your data annotation project will yield the most accurate datasets and the most specific solution to any problem. Check out our website to see the projects we’ve worked on and the services we offer, or contact us with the problem you’d like to solve!