multi-feature data fusion
Cryptographic Algorithm based Feature Level Fusion of Fingerprint and Iris in a Multi Biometric Recognition System
... auxiliary data in the biometric acknowledgment pipeline was additionally ...relevant data to improve biometric recognition exactness and (iv) performing nonstop validation utilizing auxiliary ...These ...
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A multi spectral data fusion approach to speaker recognition
... The traditional approach to identification has been to base the development of recognition sys- tems on a priori knowledge. The prior knowledge has been applied to such things as choosing the type and number of ...
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Inertial Sensor Based Modelling of Human Activity Classes: Feature Extraction and Multi-sensor Data Fusion Using Machine Learning Algorithms
... Over several years, studies of gestures and activity recognition have been confined to clinical settings and conventional lab-based equipment, such as stationary and expensive 3D motion capturing systems and force ...
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Intelligent Biometric Information Management
... and data fusion, in particular. Recent work related to data fusion [3,4] is concerned am- ong others with cross-device matching and device intero- perability, and quality dependent and ...
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Fast multi scale feature fusion for ECG heartbeat classification
... a feature-fusion method based on a multi- learning subspace-learning algorithm called GND-ICA for ECG heartbeat classification is ...vector, multi-linear subspace- learning method (GND-ICA) ...
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FEATURE LEVEL FUSION BASED MULTI-BIOMETRIC CRYPTOSYSTEM USING FUZZY VAULT FOR WIRED NETWORK
... users. Multi- biometric systems accumulate evidence from more than one biometric trait ...coverage. Multi- biometric systems require storage of multiple biometric templates for each user, which results in ...
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Marginalised Stacked Denoising Autoencoders for Robust Representation of Real Time Multi View Action Recognition
... a feature fusion approach to efficiently combine 2D observations extracted from different camera viewpoints in ...detector. Data fusion at different stages are tested and ...in ...
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Sign language recognition with multi feature fusion and Adaboost classifier
... The faster 1D models produce good recognition rates when the emphasis is only on hands. But sign language involves head, torso and face expressions along with hand movements and shapes [11]. 2D video data of signs ...
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Clustered Data Storage for Multi-Site Fusion Experiments
... by means of splitting I/O into many storage nodes. To maintain consistency among their distributed chunks, they usually need at least one metadata server or service pro- cess. On the other hand, GFS never splits a file ...
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INFORMATION FUSION FOR MULTI-SENSORY DATA
... of data and mathematical ...information fusion can be performed with different objectives such as inference, estimation, classification feature maps, abstract sensors, aggregation, and ...of ...
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Pig target tracking algorithm based on multi-channel color feature fusion
... a multi-channel color feature adaptive fusion algorithm based on histogram color similarity is proposed to improve the feature representation ability of the ...evaluation data set is ...
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Complementary feature level data fusion for biometric authentication using neural networks
... Level: Fusion at this level is the most commonly researched of all fusion levels in multi‐modal biometrics (Poh and Kittler, 2010; Nandakumar, ...and feature extraction modules perform their ...
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User Authentication Incorporating Feature Level Data Fusion of Multiple Biometric Characteristics
... The feature selection method chosen to lter keystroke dynamics data was based on normality statistics, and returned results comparable to many other research ...ngerprint feature representation ...
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Plant Recognition Based on Multi Feature and Locality Preserving Projections Fusion Algorithm
... texture feature dimension is relatively high, and affect the recognition ...LBP feature data and the feature of low dimensional LBP is ...
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Multi Feature Fusion for Video Captioning
... With the development of mobile Internet industry and big data technology, computer vision has become a hot research field. In the past, It has become an impossible task to label and describe multimedia data ...
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Application of information fusion technologies for multi source data
... information fusion can be divided into two categories: the status information fusion of the traffic flow and the characteristics information fusion of traffic ...information fusion is ...
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Joint Facial Action Unit Detection and Feature Fusion: A Multi-conditional Learning Approach
... of multi-output GP, for modeling task dependent regressors (latent functions) via GP ...input data points, the authors derived a for- mulation based on variational ...simultaneous feature ...
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Multi-feature Fusion Based Image Retrieval Scheme
... An image retrieval system helps us to retrieve the images efficiently from the databases. Text Based Image Retrieval was used in the past, but presently CBIR is being used due to its advantages compared to the former ...
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Multi-Modal and Multi-Temporal Data Fusion: Outcome of the 2012 GRSS Data Fusion Contest
... As a first step, a number of segmentation algorithms is ap- plied to the input data. Subsequently, a rule-based classification of the resulting objects is performed following the scheme in Fig. 3. The numbers at ...
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A CNN-Based Fusion Method for Feature Extraction from Sentinel Data
... estimation, in which only data already available at time t (or shortly later) can be used, and non-causal. 275[r] ...
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