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Background Modeling Algorithm for Multi-feature Fusion
2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2019In order to improve the accuracy of foreground target detection and establish a stable background model, this paper proposes a multi-feature fusion background modeling algorithm, which initializes the background model with the spatial correlation between the first frame pixel and the domain pixel, and quickly establishes the background. model.
Zhicheng Guo +3 more
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Smoke detection based on multi-feature fusion
2012 5th International Congress on Image and Signal Processing, 2012This paper discusses the application of the video image processing technology which is applied to the fire protection system. Using the characteristics of the image of the smoke when the fire broke out in the video sequence, the video monitoring scene was detected intelligently and real-time.
Dongmei Wu, Nana Wang, Hongmei Yan
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Image Retrieval Based on Multi-feature Fusion
2014 Fourth International Conference on Instrumentation and Measurement, Computer, Communication and Control, 2014In content-based image retrieval, and for this critical issue of image feature fusion, paper proposes a new method to determine the weights for multi-feature fusion. In this paper, color histogram, color correlogram, gray level co-occurrence matrix, Tamura and Hu moments, this five kinds of feature extraction method was adopted. Firstly, use these five
Dong Wenfei +4 more
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Multi-feature fusion for thermal face recognition
Infrared Physics & Technology, 2016Abstract Human face recognition has been researched for the last three decades. Face recognition with thermal images now attracts significant attention since they can be used in low/none illuminated environment. However, thermal face recognition performance is still insufficient for practical applications.
Yin Bi +4 more
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Small Components Parsing VIA Multi-Feature Fusion Network
2020 IEEE International Conference on Multimedia and Expo (ICME), 2020Part parsing is a fundamental task towards fine image understanding in the multimedia and visual field. At present, the researchers working on part parsing focus on objects with large components, such as human, car. This paper centers on segmenting objects with small components. We call it small components parsing.
Zhiying Leng, Yang Lu, Xiaohui Liang
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Predicting protein structural class based on multi-features fusion
Journal of Theoretical Biology, 2008Structural class characterizes the overall folding type of a protein or its domain and the prediction of protein structural class has become both an important and a challenging topic in protein science. Moreover, the prediction itself can stimulate the development of novel predictors that may be straightforwardly applied to many other relational areas.
Chen, Chao +3 more
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Multi-feature fusion dehazing based on CycleGAN
AI CommunicationsUnder the foggy environment, lane line images are obscured by haze, which leads to lower detection accuracy, higher false detection of lane lines. To address the above problems, a multi-layer feature fusion dehazing network based on CycleGAN architecture is proposed. Firstly, the foggy image is enhanced to remove the fog in the image, and then the lane
Wang, Jingpin +3 more
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Hand verification system based on multi-features fusion
2015 15th International Conference on Intelligent Systems Design and Applications (ISDA), 2015Human hand is a physiological biometric trait employed in order to characterize and identify a person. It is considered as one of the most popular biometric technologies especially in forensic applications, due to its high users acceptance compared to other biometric technologies.
Nesrine Charfi +3 more
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Hierarchical multi-feature fusion for multimodal data analysis
2014 IEEE International Conference on Image Processing (ICIP), 2014Multimedia data is usually represented with different low-level features, and different types of multimedia data, namely multimodal data, often coexist in many data sources. It is interesting and challenging to learn comprehensive semantics from multiple low-level features for multimodal data analysis.
Hong Zhang +3 more
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Multi feature fusion EEG emotion recognition
2021 7th International Conference on Big Data and Information Analytics (BigDIA), 2021Guo Guodong, Gao Yahan
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