Interpreting Image Classifiers by Generating Discrete Masks
IEEE Transactions on Pattern Analysis and Machine Intelligence(2022)
摘要
Deep models are commonly treated as black-boxes and lack interpretability. Here, we propose a novel approach to interpret deep image classifiers by generating discrete masks. Our method follows the generative adversarial network formalism. The deep model to be interpreted is the discriminator while we train a generator to explain it. The generator is trained to capture discriminative image regions...
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关键词
Generators,Predictive models,Electronic mail,Training,Computational modeling,Neurons,Computer science
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