Image classification is a technology that uses algorithms to analyze visual data and can help businesses improve product recommendations, enhance marketing efforts, streamline operations, and enhance the customer experience.
Some use cases of image classification:
🛍️ Improve product recommendations by analyzing customer images as well as better understand their preferences.
📈 Enhance marketing efforts by analyzing the visual content of a company's website or social media accounts to create more engaging content and improve marketing effectiveness.
🤖 Automating quality control or inventory management, which can reduce manual labor and increase efficiency 🚀.
😃 Enhance the customer experience by analyzing customer photos of a product to gain insights into product usage and areas for improvement.
There are various classification tasks, which could have a direct application into businesses:
- Food Classification - EXAMPLE CASE: which food is posted in social media about our restaurant so we know which recipes are having an impact on customer satisfaction.
Also, inside of the models folder, you have implementation of some of the most popular algorithms for image classification, as well as information (papers) related to them. The models created are the following:
- Efficientnet
- Googlenet
- Mobilenet
- Regnet
- Resnet
- Shufflenet
- Vgg