Pod 02 conducted an intensive 3-hour technical seminar in the department hardware laboratory. The session walked researchers through post-training calibration methodologies for YOLOv8n, demonstrating how careful selection of representative calibration images maintains mAP within 1.2% of baseline FP16 precision while halving inference latency.
Hands-on engineering workshop led by Pod 02 covering TensorRT model compilation, calibration dataset selection, and latency profiling on physical embedded boards.