Automatic Image Cropping for Online Classifieds | Alexey Grigorev

Automatic image cropping for online classifieds using neural networks and silence detection, with promising results in various categories and scalability considerations.

Key takeaways
  • Automatic image cropping for online classifieds is essential for enhancing user experience and increasing engagement.
  • The speaker’s approach uses a combination of neural networks and silency detection to crop images.
  • The model is tested on various categories, including cars, animals, and fashion, and shows promising results.
  • The speaker discusses the challenges of scaling the model to process large amounts of data and the need for a robust infrastructure.
  • Kubernetes is used to scale the model and handle high traffic.
  • The speaker mentions that the model is still a work in progress and that further testing and refinement are needed.
  • The use of convolutional neural networks (CNNs) is discussed, and the speaker highlights their ability to process images efficiently.
  • The speaker also mentions the concept of Deeply Supervised Skip Connections Network (DSS) and its application in image cropping.
  • The talk concludes with the speaker emphasizing the importance of collaboration between different business entities to develop and implement innovative solutions.