Dictionary learning enhancement framework: Learning a non-linear mapping model to enhance discriminative dictionary learning methods

Nonlinear Kernel Dictionary Learning Algorithm Based on Analysis Sparse Model

“…The reason we speculate may be that the error of the dataset with large dimension will increase after the kernel transformation. [42] 93.7% KSVD 93.4% LC-KSVD [42] 89.6% kernel PCA 89.0% kernel KSVD 94.5% LKDL [42] 94.1% DLE [42] 94 Besides, we also do the same classification experiment on the MNIST dataset similar to USPS dataset, in which the classification accuracy rate of analysis KSVD is still very low, only 54.8%, which also proves that the KTM method's effectiveness.…”

“…But the overall trend of the image is still similar to Fig.7, so we still set the co-sparsity of the analysis kernel KSVD algorithm for the experiment in this paper as 5. In the following, in order to demonstrate the performance of the proposed methods, we compare them with some stateof-the-art methods, for example, SRC, FDDL [39], KSVD, LC-KSVD [40], and kernel PCA, kernel KSVD [22], LKDL [41], DLE [42]. We list the results in Table 1.…”

“…The classification accuracy of KTM is 96.8%, which is second only to the analysis kernel KSVD algorithm. [39] 96.3% KSVD 96.1% LC-KSVD [41] 95.8% kernel PCA 96.0% kernel KSVD 96.9% LKDL [41] 96.0% DLE [42] 93.2% analysis kernel KSVD 97.8%…”

The Effect of Brain Based Learning Strategies and Project Based Learning on Mathematics Learning Outcomes in Students of the Kinesthetic Learning Style Group

“…Mathematics is one of the subjects that requires a high level of understanding to achieve maximum results. The learning methods and processes (Yu, Zheng, & Wang, 2019); (Abdi, Rahmati, & Ebadzadeh, 2019); (Li, Zhang, Sun, & Gao, 2019). That have been taking place using the existing curriculum have made the results achieved are not in accordance with the expectations of all parties, both parents, students and Mathematics education majors.…”