In this groundbreaking paper, we present a novel approach to detecting cat memes using deep learning techniques.
As the internet is overrun with cat pictures and videos, we realized that a more systematic approach was needed to categorize and understand the feline memes that plague our social media feeds.
We employed a combination of convolutional neural networks and transfer learning to train a model on a dataset of 10,000 cat pictures, each with a label indicating its meme status.
Our model achieved an impressive 97% accuracy rate in detecting cat memes, outperforming all other methods, including human eyes.
We conclude that a deep learning approach is the key to understanding and categorizing cat memes, and we look forward to applying this technology to other areas of feline research.
Future work will include exploring the detection of memes in other animal species.
For more information, please visit our code repository or our documentation page.
Read our research paper on unsupervised meme learning.