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The artifacts and noise in the recovered images by the regularization super-resolution (SR) algorithms based on sparse coding are obvious. A proposed SR algorithm for MRI images via two regularization parameters can improve the SR performance in this paper. With the hypothesis that the sparse coefficients in the HR space and LR space are different in the dictionary training phase while the sparse...
In order to solve the problems of face image super-resolution, a robust online dictionary learning method based on sparse representation is proposed in this paper. The online dictionary learning algorithms which can be used to train big sample datasets is introduced in the dictionary learning phase to generate better overcomplete dictionaries. Additionally, the classic L2-regularization is replaced...
Recent learning-based face super-resolution methods, such as Yang's Sparse Coding Super-Resolution (SCSR) are promising with sharp edges visually. But it also leads to obvious artifacts. In order to eliminate the artifacts, Online Dictionary Learning (ODL) algorithm is introduced in the dictionary learning phase to generate accurate overcomplete dictionary. On the other hand, the reconstruction regularization...
Some plate recognition systems can not recognize the low-resolution license plate images correctly because the resolution of the input plate image is very low. The proposed method in this paper enhances the resolution of the Chinese license plate image via sparse coding. It employs dictionary learning to get the optimal overcomplete dictionary pairs and introduces the regularization terms to recover...
Single image super-resolution via sparse coding is one of the example-based super-resolution methods. The results are promising. But the relatively low speed hinders its real-time application because of the large and complex computation. We propose a Patchwise Sparse Coding Super-Resolution algorithm to reduce the computation by processing the large mount of patches with patch dimensionality reduction...
According to the functional characters of handheld terminals, digital learning resources based on handheld terminals could be designed by means of creating situations, optimizing themes, designing efficient interactional and diverse resources. The design model is probed combined with the flow of instruction design.
A high-speed automated fingerprint SoPC identification system is designed in hardware part and software part. The pretreating process which consumes for a long time is achieved by hardware, and the matching process which consumes less time is achieved by software. This optimization improved the processing speed of system significantly.
This paper attempts to introduce affective computing into E-learning system in order to compensate and supervise learner's emotion aiming at the scarcities of emotional exchanges in E-learning. An E-learning model based on affective computing and it's function modules including the learners' emotional interface, the learners' portfolios and emotional tutor agent, as well as the key technologies are...
Assessment based on electronic portfolio is the main method to assess the performance of students' learning in web-based instructional system. In this paper, we create a quantitative assessment base on electronic portfolio to assess the quantity and quality of students' online learning including system assessment, self assessment, peer assessment and teacher assessment.
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