Large retailers across the country are shifting their focus purely on eCommerce, thanks to lockdown 2.0. For the eCommerce sector to reap the benefits of this booming phase, it must employ advanced technologies such as artificial intelligence (AI). Today, AI-powered computer vision services are beginning to optimize eCommerce sales and enhance customer’s shopping journeys by deploying machine learning algorithms. From object detection to personalized recommendations, computer vision applications for eCommerce is making giant leaps to scale the digital presence for brands across verticals.
Let’s explore some effective computer vision applications that are poised to contribute to achieving the vision of .2 trillion USD eCommerce sales in 2020.
Accelerating eCommerce Conversions with Computer Vision Applications
Here’s when artificial intelligence augments eCommerce capabilities with computer vision technologies. Powered by machine learning development services, computer vision streamlines visual classification of commercial products with the following techniques-
a) Object Detection
In contrast to manual validation and uploading, machine learning offers cost and time-effective solutions for accelerating object detection of real-world images. By training models with variable correct and incorrect image inputs, eCommerce businesses can automate-
(i) Validation of inappropriate images
(ii) Matching the right images with respective products
(iii) Extraction of features from product images
A Clothing Attribute detection model prepared by the students of Stanford University.
b) Image Classification
Image classification is a step ahead in processing eCommerce images and enhancing the overall efficiency of businesses. The high classification accuracy of machine learning models enables businesses to extract the following attributes from product images-
(i) Logo size and type
(ii) Variable color palettes
(iii) Prints and clothing patterns
(iv) Shapes of different parts like necks, sleeves, and more.
By harnessing ML models for image classification, eCommerce businesses can improve marketing campaigns, categorize products on sites, enhance customer experience significantly.
eCommerce giants, including eBay, are eliminating keywords to offer visual search for optimizing the customer experience.
The process is called “visual search”, wherein object detection, image classification, and other inputs work together to find the visually similar result of the uploaded image.
The underlying deep learning technology enables customers to look for products at eCommerce portals by uploading images. The AI system can accurately match inputs received from object detection and image classification processes to find the right product results.
a) Collaborative filtering
The neural network under collaborative filtering works on a simple logic of matching the preferences of a similar user base. It functions on the grounds that users buying similar items in the past will most likely buy certain items in the future.
Learn more: Computer Vision Applications for eCommerce
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