As computer vision dataset can be scarce in quantity, often lacks quality and needs a lot of manual labor to be useful for a computer vision model, you may need:
- To solve a problem with a strong visual component
- To detect objects that are difficult to record
- To generate datasets for computer vision
- To detect objects in changing environments
- To automate the generation of datasets for computer vision
We have a virtual sandbox environment with realistic 3D objects where objects can be recorded from different angles. This virtual environment provides the ability to place the objects in various different environments, for example varied weather conditions. This ensures that the dataset is robust and translates to your specific real world use case.
NLR can offer:
- A virtual sandbox where 3d objects can be generated realistically
- The capability to detect real world objects from generated data
- The automation of the annotation process of dataset generation
- Practically unlimited options for varying the picture angles, environments and type of objects
- Knowledge of computer vision algorithms, like YOLO
- Knowledge of data augmentation
Related Issues
- Artificial intelligence
- Computer vision
- Concept development
- Data augmentation
- Dataset generation
- Design & Analysis
- Earth observation
- Object recognition
- Operations
- Prototyping & Manufacturing
- Simulated datasets
- Synthetic datasets
- Testing
- Training
- Verification & Validation
- YOLO
- You Only Look Ones