# Countering Adversarial Images using Input Transformations

Chuan GuoMayank RanaMoustapha CisseLaurens van der Maaten

This paper investigates strategies that defend against adversarial-example attacks on image-classification systems by transforming the inputs before feeding them to the system. Specifically, we study applying image transformations such as bit-depth reduction, JPEG compression, total variance minimization, and image quilting before feeding the image to a convolutional network classifier... (read more)

PDF Abstract