Paper--Detection of False Positive and False Negative Samples in Semantic Segmentation - Code World

Paper--Detection of False Positive and False Negative Samples in Semantic Segmentation

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Origin blog.csdn.net/HLK_1135/article/details/104284409

Paper--Detection of False Positive and False Negative Samples in Semantic Segmentation

Target Detection ~ Positive and Negative Samples

Type Ⅰ error(false positive) Type Ⅱ error(false negative)

The impact of negative samples\positive samples on the performance of target detection algorithms

True rate, false positive rate, false negative rate, true negative rate of confusion matrix

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Accuracy, precision, recall, true rate, false positive rate, ROC/AUC

Data enhancement script: Use positive samples and corresponding xml files to generate negative samples in batches through random cropping (bypassing all target boxes)

Semantic Segmentation Semantic Segmentation

True and false

False rife

Positive samples produced

Paper Notes: Fully Convolutional Networks for Semantic Segmentation

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Semantic segmentation dataset converted to target detection dataset

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