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Resolution-limited statistical image classification

机译:分辨率受限的统计图像分类

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Abstract: We have examined the performance of a one-layer Perceptron for the detection and classification of small (resolution-limited) targets from their images, which are stochastic realizations of random processes. The processes are governed by non-Gaussian, non-white distributions. Our results show the potential of the Perceptron classifier as an Ideal Observer and suggest image detection and classification problems for which neural networks may be more reliable than human observers.!16
机译:摘要:我们已经检查了一层感知器对小型(分辨率受限)目标的检测和分类的性能,这些目标是随机过程的随机实现。该过程受非高斯,非白色分布的控制。我们的结果显示了Perceptron分类器作为理想观察者的潜力,并提出了图像检测和分类问题,对于这些问题,神经网络可能比人类观察者更可靠!16

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