method. This approach can identify objects in a human-like manner through text prompts and achieve high-precision recognition across different scenarios without the need for customized training.
🚀 Core Innovation
and other unique attributes of the target to achieve more accurate recognition.
🔍 Main Capabilities
Intrinsic Attribute Recognition
Object recognition based on its intrinsic attributes rather than external environment. For example: recognizing an "unripe strawberry".
Contextual Relationship Recognition
Recognizing objects based on their spatial position or relationship with other objects. For example: recognizing a "daisy on top of ice cream".
Specific Object Recognition
Precisely distinguishing specific objects within the same category to ensure accurate recognition. For example: distinguishing a "hex key set".
Dynamic State Detection
Object recognition based on motion, action, or state changes, rather than static attributes. For example: recognizing a "player in mid-air".
🧿 Trial Experience
🏭 Industry Application Cases
Agentic Object Detection has demonstrated powerful capabilities in multiple industry scenarios:
| Industry | Application Case |
|---|---|
| Assembly Verification | is correctly installed |
| Agriculture | Detecting |
| Pharmaceuticals | Identifying |
| Safety | Discovering |
| Logistics | Identifying |
| Food and Beverage | Identifying |
| Packaging | Identifying |
| Healthcare | Identifying |
| Disaster Recovery | Identifying |
| Retail and Catering | Identifying |
| Retail | Identifying |
📊 Performance Comparison
other leading teams' detection systems.
, making object recognition more intelligent, efficient, and flexible!
🔮 Future Plans for Agentic Object Detection
, making it even more powerful.
—— Identifying and tracking the dynamic changes of the target —— Simultaneously recognizing different types of objects —— Extending object detection to real-time and recorded video scenarios