A pioneer in machine intelligence, ViSenze has launched its advanced SaaS visual search technology by enhancing it with a new Automatic Object Recognition feature. It enables detection and classification of products in images, making the process of searching using images easier and faster for end consumers.
As ViSenze provides visual tech solutions to a diverse range of organizations – from e-commerce companies like Flipkart, Lazada, and Zalora, and interior design supplier Goodrich Global, to online database management company Patsnap – the company has been continuously pushing the boundaries of technology innovation for the market.
Its visual search technology allows end users to input images or image urls instead of keywords as search queries, and returns visually similar items available in the online shop or image library – based on colors, patterns, textures, shapes etc.
By enhancing this technology now with Automatic Object Recognition, it presents a game changer for businesses that are looking into further innovations to simplify the search experience for their users.
Automatic Object Recognition has the ability to automatically detect and recognize the objects present in a query image before searching for the most visually similar items. Thus, it cuts out steps in the visual search process for end users, where they no longer need to manually crop out noisy backgrounds, or select a category before they search.
The entire search process is now fully automated – from the instant an image query is uploaded, to the final generation of results – allowing for an even more streamlined, intuitive, and efficient experience for end users.
“As a pioneer in visual technology and machine intelligence space, we are constantly pushing the technology envelope to enhance the consumer experience. By making our algorithms smarter, we have created the most simple and elegant visual search user experience in the field,” said Guangda Li, Co-Founder and CTO of ViSenze.
At the moment, the Automatic Object Recognition feature is able to detect various types of items, such as tops, dresses, skirts, bottoms, shoes, bags, watches, jewelry, eyewear, and furniture. Besides further improving and fine-tuning the feature for specific cases and requirements such as deep diving into particular verticals like ethnic wear, logos and trademarks, ViSenze will be expanding into other product categories based on the needs and feedback from consumers and potential clients.
Available for both desktop and mobile platforms, the new feature can be implemented via a simple API integration on the backend.
This feature is available for testing on the company’s new demo app for Android, called Weardex.
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