complex yolo
时间: 2023-10-10 18:14:32 浏览: 105
Complex YOLO is a real-time object detection algorithm that uses a complex-valued neural network to detect objects in images. It was proposed by Peng Zhou, et al. in 2019.
The complex-valued neural network used in Complex YOLO consists of complex convolutional layers, which are able to model both the magnitude and phase information of the input data. This allows the network to capture more information about the input data compared to traditional real-valued networks.
Complex YOLO also uses a multi-task loss function that simultaneously optimizes for object detection and bounding box regression. This allows the algorithm to detect objects with high accuracy while also providing precise bounding box coordinates.
Overall, Complex YOLO is a highly accurate and efficient object detection algorithm that is capable of real-time performance on resource-limited devices.
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