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Multi-feature fusion deep networks
Neurocomputing, 2016In this paper, we propose a novel deep networks, multi-feature fusion deep networks (MFFDN), based on denoising autoencoder. MFFDN significantly reduces the classification error while giving the interpretability of the hidden-layer feature representation in learning process.
Gang Ma 0001 +3 more
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A Fuzzy Vault Scheme for Feature Fusion
2011Widespread application of biometric authentication brings about new problem of privacy. Biometric template protection is becoming a hot research. Efficient feature fusion is deemed to have good performance possibly. In this paper we proposed a fuzzy vault scheme for feature fusion. In our scheme, two facial features Multi-Block Local Binary Pattern (MB-
Lifang Wu +3 more
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Feature fusion for lung nodule classification
International Journal of Computer Assisted Radiology and Surgery, 2017This article examines feature-based nodule description for the purpose of nodule classification in chest computed tomography scanning.Three features based on (i) Gabor filter, (ii) multi-resolution local binary pattern (LBP) texture features and (iii) signed distance fused with LBP which generates a combinational shape and texture feature are utilized ...
Amal A. Farag +3 more
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Sequential Feature Fusion for Object Detection
2018In an image, the category and the location of an object are related to global, spatial and contextual visual information of the object, which are all extremely important for accurate and efficient object detection. In this paper, we propose a region-based detector named Sequential Feature Fusion Network (SFFN) which simultaneously utilizes global ...
Qiang Wang, Yahong Han
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Features Fusion for Diversity Gap Reduction
Anais do XXXI Simpósio Brasileiro de Banco de Dados (SBBD 2016), 2016Diversity has been promoted in image retrieval results using clustering algorithms to tackle queries, which refer to multiple information needs, e.g., due to ambiguity. Despite the effective results of diversity-aware methods, the image wealth of large collections and the subjectivity of human perception bring the semantic gap problem.
Iago Breno Alves do Carmo Araujo +1 more
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Feature Selection and Fusion for Texture Classification
2005In this paper, a novel texture classification method using selected and combined features from wavelet frame and steerable pyramid decompositions has been proposed. Firstly, wavelet frame and steerable pyramid decompositions are used to extract complementary features from texture regions.
Shutao Li 0001, Yaonan Wang 0001
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Feature Fusion for Pattern Recognition.
2015Information or data fusion is one of the solutions adopted for improving the performance of a pattern recognition system. Information can be gathered either from multiple data sources or through the use of multiple representations generated from a single data source.
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Feature fusion network for clothing parsing
International Journal of Machine Learning and Cybernetics, 2022Lifang Chen, Enting Yu, Honglian Cong
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Feature fusion for music detection
6th European Conference on Speech Communication and Technology, 1999Eluned S. Parris +2 more
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