Cognitive analysis and classification of apparel images

A clothing and image technology, applied in the field of cognitive analysis, can solve problems such as low conversion rate and suppliers' inability to customize quotations for individual customers

Active Publication Date: 2019-10-22
IBM CORP
View PDF5 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Vendors simply cannot tailor their offer to each individual customer due to the low conversion rate and highly personalized nature of purchases

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Cognitive analysis and classification of apparel images
  • Cognitive analysis and classification of apparel images
  • Cognitive analysis and classification of apparel images

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0013] Embodiments of the present disclosure introduce an f-score, which is a quantitative and objective description of an item of apparel. By analyzing images of clothing items using a unique Convolutional Neural Network (CNN), an f-score can be generated for each clothing item depicted in the image. In various embodiments, these f-scores can then be used to support various use cases that were not previously possible. As used herein, an item of apparel may include any fashion item, including jewelry, clothing, footwear, accessories, headwear, and the like. In many embodiments, the attributes of an item of clothing that affect how a human perceives it can be extremely subtle and include subconscious aspects that the individual is not even aware of that they are considering. Similarly, in many implementations, the concepts that determine how to analyze and classify items of apparel can vary significantly across categories and subcategories of apparel.

[0014] To resolve this...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The present invention relates to cognitive analysis and classification of apparel images. The present disclosure relates to convolutional neural networks, and more particularly, to performing cognitive analysis of images of apparel items using a customized convolutional neural network. As disclosed, f-scores can be generated for apparel items. Training images are identified, where each training image is associated with a corresponding set of tags including information about a plurality of attributes. A first convolutional neural network (CNN) is trained based on the plurality of training images and a first attribute. The first CNN is iteratively refined by, for each respective attribute, removing a set of neurons from the first CNN and retraining the first CNN based on the training imagesand the respective attribute. Upon determining that the first CNN has been trained based on each of the attributes, one or more CNNs are generated based on the first CNN. An image is received, where the image depicts an apparel item. The image is processed using the one or more CNNs, and an f-score for the apparel item is determined based on the output.

Description

Background technique [0001] The present disclosure relates to convolutional neural networks, and more particularly to utilizing a customized convolutional neural network to perform cognitive analysis of images of apparel items. [0002] Many recent advances in commerce (online commerce in particular) are often attributable to back-end analytics enabled by platforms, which help understand market demand and allow managers to fine-tune their offers to better suit customer needs and expectations. One of the fastest growing segments of the trade today encompasses fashion apparel, including accessories, footwear, clothing, jewelry, and more. Clothing item sales are a highly personalized trade category and typically involve very low conversion rates and high return rates. Due to the low conversion rate and highly personalized nature of purchases, suppliers simply cannot tailor their offers to each individual customer. There is a need for systems and methods that cognitively analyze...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06Q30/06G06V20/00
CPCG06Q30/0611G06N3/045G06F18/214G06N3/084G06V20/00G06V10/454G06V10/82G06V30/19173G06N5/022G06N3/08G06V2201/10G06F18/241
Inventor M·休厄科K·P·哈里哈兰I·费德劳夫
Owner IBM CORP
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap