Optimizing the Detection Model and Spatial Integration

Reshaping AI model to optimize detection

Advancing our detection capabilities remained a top priority throughout this phase, and we dedicated significant efforts to experimenting with a range of different model architectures. Our primary objective was to enhance both the accuracy and speed of the detection system, ensuring that it can effectively meet the demands of real-time applications. As part of this initiative, we integrated the model with a state-of-the-art geomatics locator, which greatly improved its ability to determine spatial positions with increased efficiency and precision. This integration has allowed the system to pinpoint locations with greater accuracy, significantly boosting its overall performance. Through rigorous testing, analysis, and iterative refinements, we have made considerable progress in moving closer to our goal of achieving a real-time, high-precision detection system capable of operating seamlessly in dynamic environments with minimal delays.

Key Achievements:

• Tested different model architectures for improved detection accuracy and speed.
• Integrated the model with a geomatics locator for spatial positioning.
• Enhanced detection efficiency through iterative refinements.