How to Use Deep Learning in Visual Search?
Deep learning is a part for machine learning process to apprehend the data used for training the machines with algorithms. And, now deep learning is also playing a bigger role in visual search technology to make image based searching more personalize and productive.
Deep learning is used in visual search to make the search results more relevant. A large amount of data is used in conjunction with deep learning algorithms to develop the visual search work perfectly and give the most suitable or relevant results.
Actually, Visual search uses deep learning to find and display images, shown to users on search engines. Visual Search Deep Learning programs can recognize items of searched for an example, if someone wore a clothing item and you can click and pull up images of related clothing using the visual search technology. It can also do things such as recognize a holiday destination, then, having done so, bring up images of the same holiday destination.
The main motive of deep learning is to make search engine understand what’s in an image, so as to give people exactly what they want. Most of the ecommerce companies are now offering visual search based results to make online shopping more personalize as per user’s preferences. Besides, ecommerce companies, leading tech giants like Google, Facebook, Microsoft and Apple are also heavily investing into visual search technology to explore new opportunities and make the results better.
If you are looking for someone to meet your visual search needs, you can hire Cogito that offers a complete visual search solution for ecommerce and other industries. Cogito helps to integrate deep learning with right mix of algorithms and online searchers or customers increase the engagement and conversion rates while enhancing the recommendation engine with visual signal to give more relevant results and make the online searching more personalized.
