The authors investigate how to introduce invariant features to speech recognition neural networks using conventional back propagation (BP), K-neighbor interpolation training (KNIT) with a number of time-shifted exampl...
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The authors investigate how to introduce invariant features to speech recognition neural networks using conventional back propagation (BP), K-neighbor interpolation training (KNIT) with a number of time-shifted examples (TSEs) of the same training sample. The TSEs are employed for training of a multilayer perceptron (MLP) and a time-delay neural network (TDNN) structure to enrich the training sample set covering a larger area of phoneme sample space. Speaker-dependent phoneme recognition experiments were performed. The advantages and disadvantages of using time-shifted examples of a training sample for a MLP and a TDNN structure and a BP and a KNIT algorithm are discussed.< >
Describes a method for extracting nonrigid moving objects. Every moving object may be approximated by a set of iso-intensity patches. The method finds the motions of these patches by integrating the locations and the ...
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Describes a method for extracting nonrigid moving objects. Every moving object may be approximated by a set of iso-intensity patches. The method finds the motions of these patches by integrating the locations and the intensities of temporal edges. Then, it finds the objects by finding clusters among the motions of the patches. The proposed method can extract many nonrigid objects on a complicated background. The performance of the proposed method was tested successfully on extracting pedestrians from a cinematic sequence viewing a street crossing.< >
A closed-loop image segmentation system that incorporates a genetic algorithm to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions is presented. The genetic...
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A closed-loop image segmentation system that incorporates a genetic algorithm to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions is presented. The genetic algorithm efficiently searches the hyperspace of segmentation parameter combinations to determine the parameter set which maximizes the segmentation quality criteria. A summary of the experimental results that demonstrates the ability to perform adaptive image segmentation and to learn from experience using a collection of outdoor color imagery is given.< >
This book provides several efficient Kalman filters (linear or nonlinear) under information theoretic criteria. They achieve excellent performance in complicated non-Gaussian noises with low computation complexity and...
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ISBN:
(数字)9783031337642
ISBN:
(纸本)9783031337635;9783031337666
This book provides several efficient Kalman filters (linear or nonlinear) under information theoretic criteria. They achieve excellent performance in complicated non-Gaussian noises with low computation complexity and have great practical application potential. The book combines all these perspectives and results in a single resource for students and practitioners in relevant application fields. Each chapter starts with a brief review of fundamentals, presents the material focused on the most important properties and evaluates comparatively the models discussing free parameters and their effect on the results. Proofs are provided at the end of each chapter. The book is geared to senior undergraduates with a basic understanding of linear algebra, signal processing and statistics, as well as graduate students or practitioners with experience in Kalman filtering.
This book constitutes the refereed proceedings of the Third International Conference on Social robotics, ICSR 2011, held in Amsterdam, The Netherlands, in November 2011. The 23 revised full papers were carefully selec...
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ISBN:
(数字)9783642255045
ISBN:
(纸本)9783642255038
This book constitutes the refereed proceedings of the Third International Conference on Social robotics, ICSR 2011, held in Amsterdam, The Netherlands, in November 2011. The 23 revised full papers were carefully selected during two rounds of reviewing and improvement from 51 submissions. The papers are organized in topical sections on social interaction with robots; nonverbal interaction with social robots; robots in society; social robots in education; affective interaction with social robots; robots in the home.
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