Overview
The beneficiary of our services, a global leader listed in the top 100 Forbes companies with over 100 billion EUR in revenues, operates across multiple high-tech industries, including Consumer Electronics, Home Appliances, Home Entertainment, Mobile Communications, Solar, and Display Technologies.
The challenge presented to us was both unique and complex – to develop an image recommendation system tailored for the visual arts and creative industries. This system needed to parallel the efficiency and accuracy of Google’s image search but with a focus on catering to the nuanced demands of creative professionals and art enthusiasts.
One of the main goals was to seamlessly integrate a sophisticated visual search capability that could understand and interpret artistic content, thereby revolutionizing how users discover and interact with visual arts online.
Our solution
To tackle this challenge, we designed a cutting-edge solution leveraging Convolutional Neural Networks (CNN), the pinnacle of image recognition technology. Our approach was methodical and the system entailed two distinct phases:
- an offline phase focused on model training and tuning, alongside feature extraction
- an online phase dedicated to image query and retrieval
This dual-phase process lays a solid foundation for the system to accurately understand and categorize images, ensuring efficient matching of user queries with relevant visual content.
By incorporating state-of-the-art technologies, our solution addresses the specific demands of the creative industries and enhances the capabilities of image recommendation systems.
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