intelligent deep learning based product image recommendation and classification system

Recently, recommendation system (RS) has gained significant attention in several industries and business sectors. At the same time, image is also found helpful to determine relevant objects that exist form of image. It mainly based on extraction different features utilize it get recommended outcomes. The recently developed deep learning (DL) models can be applied design effective product classification systems. In this aspect, paper designs an intelligent enabled (IDL-PIRC) system. proposed IDL-PIRC technique aims examine input recommend classify products user query. addition, involves Gaussian filtering (GF) pre-processing eradicate existence noise it. Moreover, fusion-based feature uses Grey-Level Run Length Matrix (GLRLM) Residual Network (ResNet152) models. Furthermore, kNN ranking approach employed for cascaded neural network (CNN) utilized classification. A wide range simulations take place results are inspected interms evaluation parameters.