The hybrid networks were constructed in the PyTorch framework and Python-3.9 with Intel Core i7 CPU and NVIDIA GTX 1650Ti GPU. Meanwhile, we used the Nao Robot from Softbank Robotics (Issy-les-Moulineaux, France) for humanoid part. We chose BCELoss as the loss function, Adam as the optimi...
We used the PyTorch implementation of YOLOv8 (available at: https://github.com/ultralytics/ultralytics (accessed on 28 November 2023)), developed by the Ultralytics LLC and the YOLOAir’s implementation of C3STR (available at: https://github.com/iscyy/yoloair (accessed on 28 November ...
In this study, experiments were conducted using PyTorch 2.0.0 based on GPU for the experimental setup. PyTorch utilizes CUDA 11.8 to support the parallel computation of the YOLOv8 deep learning model. Leveraging GPU and CUDA, we accelerated the computational processes and employed the PyTorch framew...