N. Saparkhojayev, Lazzat Zholayeva, Yerzhan Tashkenbayev, D. Tokseit
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引用次数: 1
摘要
定向梯度直方图(Histogram of Oriented Gradient, HOG)是一种常用的图像目标识别算法，具有很高的成功率。在图像处理技术中，硬件增强是研究大尺寸、复杂图像的关键特征之一。在本研究中，从图像区域上密集网格的所有位置提取HOG特征，并使用线性支持向量机(SVM)对组合特征进行分类。
Abnormality Detection in Chest X-ray Images Using Uncertainty Prediction Algorithms
Histogram of Oriented Gradient (HOG) is one of the popular algorithms for recognizing objects in images with a very high success rate. In image processing techniques hardware reinforcement is one of the key features of studying the large size and complex images to perform. In this study, HOG features were extracted from all locations of a dense grid on an image region and used linear Support Vector Machine (SVM) to classify the combined features.
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