I. Haritha, M. Harshini, Shruti Patil, Jeethu Philip
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引用次数: 0
摘要
本研究的目的是利用You Look Only Once (YOLO)方法进行目标检测。该方法在速度和性能上都比现有模型有效。一些算法在单次前向传播中没有扫描所有区域,但在YOLO中,算法通过使用卷积神经网络和类机会预测绑定框来分析整个图像。与其他算法相比,YOLO的执行速度更快。
This research work aims to perform object detection by using the You Look Only Once (YOLO) method. This method is much efficient to the existing models in terms of speed and performance. Some of the algorithms do not scan all the regions in single forward propagation but in YOLO, the algorithm analyzes the entire image by predicting binding boxes using convolutional neural network and class opportunities. YOLO performs faster when compared to other algorithms.