7 Papers
Jiahua Wu is an academic researcher from Jiangxi University of Finance and Economics. The author has contributed to research in topics: Computer science & Image fusion. The author has an hindex of 4, co-authored 6 publications.
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Papers
Multilevel Features Convolutional Neural Network for Multifocus Image Fusion
TL;DR: A novel multilevel features convolutional neural network (MLFCNN) architecture for image fusion that outperforms some state-of-the-art image fusion algorithms in terms of both qualitative and objective evaluations is proposed.
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Multimodal Medical Image Fusion Based on Fuzzy Discrimination With Structural Patch Decomposition
TL;DR: A novel multimodal medical image fusion method based on structural patch decomposition (SPD) and fuzzy logic technology that outperforms state-of-the-art methods in terms of subjective visual and quantitative evaluations is proposed.
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Multiexposure Estimation and Fusion Based on a Sparsity Exposure Dictionary
TL;DR: A novel exposure estimation-based MEF method with sparse decomposition and a designed sparsity exposure dictionary (SED) that outperforms the state-of-the-art methods in terms of subjective visual and quantitative evaluations.
15
Multi-Focus Image Fusion Based on a Non-Fixed-Base Dictionary and Multi-Measure Optimization
TL;DR: A novel multi-focus image fusion method based on a non-fixed-base dictionary and multi-measure optimization is presented in the non-subsampled shearlet transform (NSST) domain and yields a better effect than other methods in both the visual quality and the objective assessment.
The Dynamic Vectors-Based Attention Model for Chinese Mathematical Term Extraction
TL;DR: In this article , the authors constructed a secondary school mathematics corpus and proposed a model to resolve the problems of polysemy of one character problem and nested terms problem, termed BERT-LLA-CRF, which integrates attention mechanisms and Chinese character information to solve the nested terminology problem.