Abstract: A domain adaptation system and method for identifying similar images of fashion products is provided. The system includes a memory having computer-readable instructions stored therein and a processor. The processor is configured to access a plurality of source images of a plurality of fashion products. The processor is further configured to access a plurality of target images of the plurality of fashion products. The processor is configured to process the source images and the target images to determine one or more domain invariant features from the source and target images. Further, the processor is configured to identify one or more substantially similar images from the source images and the target images based upon the one or more domain invariant features.

Abstract: System and method for predicting discount-demand elasticity of one or more retail items in a portfolio are presented. The system includes a feature engineering module configured to generate a plurality of features based on historical data of a plurality of retail items in the portfolio. The system further includes an elasticity estimator configured to estimate discount-demand elasticity values for the plurality of retail items in the portfolio; and an elasticity-band generator configured to generate a set of elasticity bands for the plurality of retail items based on the estimated discount-demand elasticity values. The system furthermore includes a training module configured to train a classification model based on the generated plurality of features and the generated set of elasticity bands. The system moreover includes an elasticity prediction module configured to generate discount-demand elasticity of the one or more retail item in the portfolio from the trained classification model.

Abstract: System and method for optimizing prices of a plurality of retail items in a portfolio are presented. The system includes a demand estimator and a price optimizer including a return computation module, a price configuration generator and a price configuration selector. The demand estimator is configured to estimate a set of demand values for the plurality of retail items at a plurality of discount levels. The return computation module is configured to compute return on investment (ROI) values for the plurality of retail items. The price configuration generator is configured to generate a plurality of price configurations for the plurality of retail items and the price configuration selector is configured to select an optimum price configuration from the plurality of price configurations based on a sales target for the portfolio.

Abstract: A domain adaptation system and method for identifying similar images of fashion products is provided. The system includes a memory having computer-readable instructions stored therein and a processor. The processor is configured to access a plurality of source images of a plurality of fashion products. The processor is further configured to access a plurality of target images of the plurality of fashion products. The processor is configured to process the source images and the target images to determine one or more domain invariant features from the source and target images. Further, the processor is configured to identify one or more substantially similar images from the source images and the target images based upon the one or more domain invariant features.

Abstract: A system and method for determining organic sellability of fashion products is provided. The system includes a memory having computer-readable instructions stored therein. The system further includes a processor configured to access a plurality of fashion images of a plurality of fashion products. The processor is configured to acquire sales data corresponding to each of the plurality of fashion products. The processor is further configured to identify one or more substantially similar fashion styles of the fashion products based upon the plurality of fashion images and attributes corresponding to the fashion products. In addition, the processor is configured to create one or more training sets having pairs of the identified similar fashion styles. Each of the similar fashion styles is associated with corresponding merchandising features.

Abstract: A method to determine image similarities. The method may include obtaining a first image and a second image and determining a discrete transform difference between a first discrete transform of the first image and a second discrete transform of the second image. The method may also include determining multiple first intensity vectors for the first image and determining multiple second intensity vectors for the second image. The method may also include determining an intensity vector difference between the multiple first intensity vectors and the multiple second intensity vectors and determining a color difference between a first color histogram of the first image and a second color histogram of the second image. The method may also include determining a similarity between the first image and the second image based on the discrete transform difference, the intensity vector difference, and the color difference.

Abstract: A method to determine image similarities. The method may include obtaining a first image and a second image and determining a discrete transform difference between a first discrete transform of the first image and a second discrete transform of the second image. The method may also include determining multiple first intensity vectors for the first image and determining multiple second intensity vectors for the second image. The method may also include determining an intensity vector difference between the multiple first intensity vectors and the multiple second intensity vectors and determining a color difference between a first color histogram of the first image and a second color histogram of the second image. The method may also include determining a similarity between the first image and the second image based on the discrete transform difference, the intensity vector difference, and the color difference.

Abstract: A method to determine image similarities. The method may include obtaining a first image and a second image and determining a discrete transform difference between a first discrete transform of the first image and a second discrete transform of the second image. The method may also include determining multiple first intensity vectors for the first image and determining multiple second intensity vectors for the second image. The method may also include determining an intensity vector difference between the multiple first intensity vectors and the multiple second intensity vectors and determining a color difference between a first color histogram of the first image and a second color histogram of the second image. The method may also include determining a similarity between the first image and the second image based on the discrete transform difference, the intensity vector difference, and the color difference.

Abstract: A method to determine image similarities. The method may include obtaining a first image and a second image and determining a discrete transform difference between a first discrete transform of the first image and a second discrete transform of the second image. The method may also include determining multiple first intensity vectors for the first image and determining multiple second intensity vectors for the second image. The method may also include determining an intensity vector difference between the multiple first intensity vectors and the multiple second intensity vectors and determining a color difference between a first color histogram of the first image and a second color histogram of the second image. The method may also include determining a similarity between the first image and the second image based on the discrete transform difference, the intensity vector difference, and the color difference.