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What is Sensors 25 04138 about?
This paper presents a dynamic Kalman filtering method for multi-object fruit tracking and counting in complex orchard environments, integrating an improved YOLO-based detection algorithm with a dynamically optimized Kalman filter. The proposed system enhances detection accuracy and tracking stability by addressing challenges such as occlusion and motion blur, achieving high performance metrics like a MOTA of 95.0% and a coefficient-of-determination of 0.85 for fruit counting. Experimental results demonstrat
- Author
- ishumandal159
- Language
- EN