April 2016 Summaries

Where's Waldo serves as an intriguing dataset for testing a visual recognition API through Custom Training, as demonstrated during a Hack Day project at Clarifai. The project involved using a pre-existing dataset of 19 Where's Waldo maps, divided into labeled tiles, and expanding it with additional maps to train a model to identify Waldo. Initial testing showed low detection rates, especially in complex scenes, due to the abundance of non-Waldo elements. Adjustments were made by manually removing potential false-positive lookalikes from training data, which improved accuracy but still faced challenges with busy scenes and unexpected false positives. The project highlighted the iterative nature of machine learning, emphasizing the need for more balanced and Waldo-positive examples to enhance model accuracy. Users interested in similar machine learning projects can explore these techniques through Clarifai's Custom Training platform.

Clarifai's Not Safe for Work (NSFW) adult content recognition model is an innovative tool available via their API, designed to accurately identify and manage images and videos containing nudity or semi-nudity. By providing a probability rating for content being Safe for Work (SFW) or Not Safe for Work (NSFW), the model allows users to filter, flag, or curate content according to their needs, with impressive precision in distinguishing between explicit and non-explicit material. This NSFW model is particularly useful for platforms with user-generated content, such as marketplaces and social media sites, to protect users from unsolicited adult content and ensure community standards are upheld. Additionally, some adult content sites leverage the model to curate and highlight specific content effectively. The model's accuracy is touted as being superior to past mistakes made by other platforms, such as confusing innocuous items for explicit content.