A Multimodal Pattern Recognition Framework for Speaker Detection
標(biāo)簽： Recognition Multimodal Framework Detection
上傳時間： 2013-11-26
上傳用戶：caozhizhi
Description: FASBIR(Filtered Attribute Subspace based Bagging with Injected Randomness) is a variant of Bagging algorithm, whose purpose is to improve accuracy of local learners, such as kNN, through multi-model perturbing ensemble. Reference: Z.-H. Zhou and Y. Yu. Ensembling local learners through Multimodal perturbation. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, 2005, vol.35, no.4, pp.725-735.
標(biāo)簽： Description Randomness Attribute Filtered
上傳時間： 2015-04-10
上傳用戶：ynzfm
A dissipative particle swarm optimization is developed according to the self-organization of dissipative structure. The negative entropy is introduced to construct an opening dissipative system that is far-from-equilibrium so as to driving the irreversible evolution process with better fitness. The testing of two Multimodal functions indicates it improves the performance effectively. structure. The negative entropy is introduced to construct an opening dissipative system that is far-from-equilibrium so as to driving the irreversible evolution process with better fitness. The testing of two Multimodal functions indicates it improves the performance effectively.
標(biāo)簽： self-organization optimization dissipative developed
上傳時間： 2016-03-31
上傳用戶：zgu489
The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming Multimodal images. Component images forming Multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. The term image registration is most commonly used to denote the process of alignment of images , that is of transforming them to the common coordinate system. This is done by optimizing a similarity measure between the two images. A widely used measure is Mutual Information (MI). This method requires estimating joint histogram of the two images. Experiments are presented that demonstrate the approach. The technique is intensity-based rather than feature-based. As a comparative assessment the performance based on normalized mutual information and cross correlation as metric have also been presented.
標(biāo)簽： present modalities existence different
上傳時間： 2017-04-03
上傳用戶：qunquan
-The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming Multimodal images. Component images forming Multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. Mutual Information is the similarity measure used in this case for optimizing the two images. This method requires estimating joint histogram of the two images. The fusion of images is the process of combining two or more images into a single image retaining important features from each. The Discrete Wavelet Transform (DWT) has become an attractive tool for fusing Multimodal images. In this work it has been used to segment the features of the input images to produce a region map. Features of each region are calculated and a region based approach is used to fuse the images in the wavelet domain.
標(biāo)簽： present modalities existence different
上傳時間： 2014-03-04
上傳用戶：15736969615
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