How can we better utilize Synthetic Data? : Synthetic Data 5 Use-Cases
Table of Contents
Synthetic data is gaining attention as a substitute that can complement actual real data. Often, Real data available for use is biased or restricted due to security reasons. Synthetic data has the advantage of protecting the privacy of original data and diversifying datasets, thus contributing to research and learning. Let’s take a look at the various types of Synthetic data and their application.
Synthetic Data Use-Cases
1. Text data
- Training data for emotion classification, semantic analysis in Data Science, Machine Learning
- Interactive interfaces like Chatbots
- Personalized advertising messages
- Inspiring creative contents such as novel, poem
2. Tabular data
- Data modeling, prediction, classification in Data Science, Machine Learning
- Customer analysis in financial services
- Patient management, Disease Classification and prediction in healthcare
- Industrial process optimization and quality control
3. Image data
- Object recognition, Image classification in Computer Vision
- Disease Classification and diagnosis via X-ray, MRIs, CT
- Pedestrian detection and driving simulations for Autonomous vehicles
- Generating diverse facial images across different races, genders, and ages for face recognition
4. Video data
- Behavior analysis, Object recognition, Emotion analysis in Computer Vision
- Traffic flow analysis and Driver behavior study for traffic planning
- Analyzing and establishing Sports game strategies
- Virtual Reality(VR) and animation production in entertainment industry
5. Audio data
- Diverse languages, accents, and pronunciations for Voice Recognition systems
- Producing audio books and document reading services
- Creating language learning materials with varied languages and pronunciations
As such, Synthetic data is applicable in various aspects of our lives. Its demand is high as it can be utilized in numerous real-life scenarios. Synthetic data is becoming more realistic and diverse, showing high potential for growth.
To widen its application across broader domains, efforts are needed to enhance the quality of Synthetic data to convincingly replace Real data. Moreover, ethical use and protection of sensitive information are paramount.
At CUBIG, We offer a service that enables you to create the facial images across different races, genders, and ages. If interested, click the link for more information! : https://pixaid.ai/