A5064788213- Advanced Image and Video Retrieval Techniques
- Image and Signal Denoising Methods
- Traditional Chinese Medicine Studies
- Advanced Image Processing Techniques
- Image Retrieval and Classification Techniques
- Advanced Numerical Analysis Techniques
- Medical Image Segmentation Techniques
- Genomics and Phylogenetic Studies
- Advanced Image Fusion Techniques
- Image Processing Techniques and Applications
- Multimodal Machine Learning Applications
- 3D Shape Modeling and Analysis
- Advanced Vision and Imaging
- Face recognition and analysis
- Computer Graphics and Visualization Techniques
- Polysaccharides and Plant Cell Walls
- Visual Attention and Saliency Detection
- Color perception and design
- Image Enhancement Techniques
- Domain Adaptation and Few-Shot Learning
- Stock Market Forecasting Methods
- Chromosomal and Genetic Variations
- Algorithms and Data Compression
- Video Surveillance and Tracking Methods
- Simulation and Modeling Applications
Shandong University of Finance and Economics
2015-2024
Hainan University
2024
Red Cross Society of China
2024
Xinjiang Medical University
2021-2022
Chengdu University of Traditional Chinese Medicine
2014-2021
North Minzu University
2021
Liaoning University of Technology
2015-2021
Shandong University of Science and Technology
2008-2020
Wuhan University of Technology
2019
Shandong University
2011-2018
To recover the corrupted pixels, traditional inpainting methods based on low-rank priors generally need to solve a convex optimization problem by an iterative singular value shrinkage algorithm. In this paper, we propose simple method for image using low rank approximation, which avoids time-consuming shrinkage. Specifically, if similar patches of are identified and reshaped as vectors, then patch matrix can be constructed collecting these patch-vectors. Due its columns being highly linearly...
In ocean engineering, an underwater vehicle is widely used as important equipment to explore the ocean. However, due reflection and attenuation of light when propagating in water, images captured by visual system complex environment usually suffer from low visibility, blurred details, color distortion. To solve this problem, article, we present image enhancement framework based on transfer learning, which consists a domain transformation module module. The two modules, respectively, perform...
Abstract Background Insomnia as one of the dominant diseases traditional Chinese medicine (TCM) has been extensively studied in recent years. To explore novel approaches research on TCM diagnosis and treatment, this paper presents a strategy for insomnia based machine learning. Methods First all, 654 cases have collected from an experienced doctor sample data. Secondly, light characteristics contents samples divided into four parts: basic information, diagnostic methods, treatment syndrome...
Due to the interaction of many factors in stock market, price prediction has always been a challenging problem field machine learning. In particular, mutation market often have great impact on subsequent predictions. The existing models seldom consider impacts other stocks and points accuracy target stocks. Therefore, this paper presents new knowledge graph deep learning method combined with network focusing related points. First, features are obtained through ConvLSTM network. Second, is...
Although video deraining technology has achieved great success in recent years, extracting spatiotemporal feature representations across the domains of spatial and temporal successive frames, then performing modeling, restoring high-quality videos with rich details are still challenging tasks. In this paper, we use hybrid Transformer for first attempt rain removal tasks, propose a novel network based on transformer (VDN-HT) to aggregate global local accomplish deraining. extraction process,...
The popularity of social computing and sentiment analysis has attracted an increasing attention tourism industry academia. residents' tourists' plays important role to the development tourism. It aims identify analyze opinions emotions contained in reviews which are expressed by residents or tourists. Although it's a challenging task, many companies research institutes developing web services provide public-access cost-effective solutions problem. However, best our knowledge, there very few...
In solving classification problems in the field of machine learning and pattern recognition, pre-processing data is particularly important. The processing high-dimensional feature datasets increases time space complexity computer reduces accuracy models. Hence, proposal a good selection method essential. This paper presents new algorithm for selection, retaining mutation operators from traditional genetic algorithms. On one hand, global search capability ensured by changing population size,...
Abstract Automatic and accurate instance segmentation of teeth can provide important support for computer‐aided orthodontic work. Traditional methods tooth studies often ignore the rich structural features teeth. Capturing complete geometry as well morphological details a single remains challenge current studies. In this article, new deeplearning network based on capturing dependencies receptive field adjustment in cone beam computed tomography (CBCT) is proposed to achieve automatic dental...
Accurate segmentation of the tongue body is an important prerequisite for computer‐aided diagnosis. In general, size and shape are very different, color similar to surrounding tissue, edge fuzzy, some interfered by pathological details. The existing methods often not ideal image processing. To solve these problems, this paper proposes a symmetry edge‐constrained level set model combined with geometric features segmentation. Based on geometry tongue, novel initialization method proposed...
Although it is frequently observed that aligning short reads to genomes becomes harder if they contain complex repeat patterns, there has not been much effort quantify the relationship between complexity of and difficulty short-read alignment. Existing measures sequence seem unsuitable for understanding quantification this relationship. We investigated several found length-sensitive had highest correlation accuracy In particular, rate distinct substrings length k, where k similar read...
During the annotation procedure of salient object detection, researchers usually locate approximate location objects first and then process pixels that need to be finely annotated. Following this idea, we find existing methods have limited exploration for solving problem positioning objects. Furthermore, no effective solution has been proposed hard-sample related task. Therefore, propose dynamic scale-aware learning learn scale weights vary with different images solve problem. Second, design...