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README.md

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 > <img src="./assets/icons/firework.png" style="height:20px;"> (New!) Added Tutorial to generate adversarial images for ResNet-50 using Stable Diffusion.
 
 
-## <img src="./assets/icons/contributions.png" style="height:20px;"> Key Contributions:
+## <img src="./assets/icons/contributions.png" style="height:35px;"> Key Contributions:
 
 - We propose a black-box algorithmic framework based on an Evolutionary Strategy titled EvoSeed to generate natural adversarial samples in an unrestricted setting.
 - Our results show that adversarial samples created using EvoSeed are photo-realistic and do not change the human perception of the generated image; however, can be misclassified by various robust and non-robust classifiers.
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 Figure: Adversarial images created with EvoSeed are prime examples of how to deceive a range of classifiers tailored for various tasks.
 Note that, the generated natural adversarial images differ from non-adversarial ones, suggesting the adversarial images' unrestricted nature.
 
-## <img src="./assets/icons/mortarboard.png" style="height:20px"> Tutorial:
+## <img src="./assets/icons/mortarboard.png" style="height:35px"> Tutorial:
 Tutorial for creating adversarial images for ResNet-50 using Stable Diffusion can be found in the [notebook](./code/Tutorial.ipynb)
 
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@@ -40,7 +40,7 @@ Tutorial for creating adversarial images for ResNet-50 using Stable Diffusion ca
 
 
 
-## <img src="./assets/icons/cite.png" style="height:20px"> Citation:
+## <img src="./assets/icons/cite.png" style="height:35px"> Citation:
 
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