Adaptively Enhancing Facial Expression Crucial Regions via a Local Non-local Joint Network

Facial expression recognition(FER)is still challenging due to the small interclass discrepancy in facial expression data.In view of the significance of facial crucial regions for FER,many existing studies utilize the prior information from some annotated crucial points to improve the performance of FER.However,it is complicated and time-consuming to manually annotate facial crucial points,especially for vast wild expression images.Based on this,a local non-local joint network is proposed to adaptively enhance the facial crucial regions in feature learning of FER in this paper.In the proposed method,two parts are constructed based on facial local and non-local information,where an ensemble of multiple local networks is proposed to extract local features corresponding to multiple facial local regions and a non-local attention network is addressed to explore the significance of each local region.In particular,the attention weights obtained by the non-local network are fed into the local part to achieve interactive feedback between the facial global and local information.Interestingly,the non-local weights corresponding to local regions are gradually updated and higher weights are given to more crucial regions.Moreover,U-Net is employed to extract the integrated features of deep semantic information and low hierarchical detail information of expression images.Finally,experimental results illustrate that the proposed method achieves more competitive performance than several state-of-the-art methods on five benchmark datasets.

An aerospace bracket designed by thermo-elastic topology optimization and manufactured by additive manufacturing

Combination of topology optimization and additive manufacturing technologies provides an effective approach for the development of light-weight and high-performance structures.A heavy-loaded aerospace bracket is designed by topology optimization and manufactured by additive manufacturing technology in this work.Considering both mechanical forces and temperature loads,a formulation of thermo-elastic topology optimization is firstly proposed and the sensitivity analysis is derived in detail.Then the procedure of numerical optimization design is presented and the final design is additively manufactured using Selective Laser Melting(SLM).The mass of the aerospace bracket is reduced by over 18%,benefiting from topology and size optimization,and the three constraints are satisfied as well in the final design.This work indicates that the integration of thermo-elastic topology optimization and additive manufacturing technologies can be a rather powerful tool kit for the design of structures under thermal-mechanical loading.