Hanmin Ye^1,2, Yinghui Zhou¹, Xiaomei Tao^3,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1709-1732, 2023, DOI:10.32604/csse.2023.039186

Abstract With the popularity of online learning and due to the significant influence of emotion on the learning effect, more and more researches focus on emotion recognition in online learning. Most of the current research uses the comments of the learning platform or the learner’s expression for emotion recognition. The research data on other modalities are scarce. Most of the studies also ignore the impact of instructional videos on learners and the guidance of knowledge on data. Because of the need for other modal research data, we construct a synchronous multimodal data set for analyzing learners’ emotional states in online learning… More >

Jia-Yu Liang¹, Hong-Bo Zhang^1,*, Qing Lei², Ji-Xiang Du³, Tian-Liang Lin⁴

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3243-3256, 2023, DOI:10.32604/iasc.2023.035812

Abstract Monocular 6D pose estimation is a functional task in the field of computer vision and robotics. In recent years, 2D-3D correspondence-based methods have achieved improved performance in multiview and depth data-based scenes. However, for monocular 6D pose estimation, these methods are affected by the prediction results of the 2D-3D correspondences and the robustness of the perspective-n-point (PnP) algorithm. There is still a difference in the distance from the expected estimation effect. To obtain a more effective feature representation result, edge enhancement is proposed to increase the shape information of the object by analyzing the influence of inaccurate 2D-3D matching on… More >