Titlebook: Artificial Intelligence on Fashion and Textiles; Proceedings of the A Wai Keung Wong Conference proceedings 2019 Springer Nature Switzerlan

口味

Costume Expert Recommendation System Based on Physical Features,erence engine, namely, blackboard model algorithms to obtain the recommended costume that suits the physical features of the customer. Therefore, the proposed system provides customers an intelligent costume recommendation strategy in accordance with SVM and Expert System.

figurine

Sparse Discriminant Principle Component Analysis,vatives, the number of the modified PCs of SDPCA is not limited by the number of class, namely, SDPCA can address the small-class problem in LSR based methods. To solve the optimization problem, we also propose a new algorithm. Experimental results on product dataset, face dataset and character dataset demonstrate the effectiveness of SDPCA.

運動吧

The CF+TF-IDF TV-Program Recommendation,is to infer users’ preference from their viewing habits and the program type they choose. By using CF+TF-IDF, we build a TV-program recommendation model, aiming at improving users’ viewing experience.

樹上結(jié)蜜糖

整體

Sikhar Patranabis,Debdeep Mukhopadhyayages, the network model can efficiently extract discriminative features and achieve a retrieval accuracy of 99.89% on our test set. This performance maintains well when simpler deep architecture is used, but decreases quickly if the contents of fed fabric image are reduced.

prosperity

MIR

Network Configurations and Models,clothing knowledge base and clarify the recommendation rules. Considering the characteristics of the customers and the selection criteria, this system can make personalized clothing recommendation scheme for customers and ensure the rationality of the recommendation results.

手術(shù)刀

Sikhar Patranabis,Debdeep Mukhopadhyayated information to the classic itti visual attention model, we achieve the multi-object attention model of the clothing style. And based on this we implemented the autonomous development of clothing style recognition by Multi-Layer In-place Learning Network (MILN in short). Experiments prove the feasibility and effectiveness of our model.

Crepitus

A Clothing Recommendation System Based on Expert Knowledge,clothing knowledge base and clarify the recommendation rules. Considering the characteristics of the customers and the selection criteria, this system can make personalized clothing recommendation scheme for customers and ensure the rationality of the recommendation results.

MELD