Machine-learning potential for silver sulfide: From CHGNet pretraining to DFT-refined phase stability

· · 来源:dev资讯

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“When I saw this stuff on Instagram and self harm, my brain immediately goes, ‘how good is their model? How well are they going to be detecting this?’” he added.

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While this is immediately effective, the random perturbations introduce a disturbing texture that can obfuscate details in the original image. To counter this, we can make some smart choices on where and by how much to perturb our input image in an attempt to add some structure to our dither and preserve some of the lost detail.