Due to advancements in brain signal application technology, there has been a growing focus on the human speech Brain-computer Interface (BCI) in recent years. An essential initial phase in crafting speech recognition ...
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This work presents a novel semi-supervised dictionary learning framework that updates the dictionary by online learning and is efficient in utilizing the training data. The method employs a two-stage process to train ...
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ISBN:
(数字)9798331506520
ISBN:
(纸本)9798331506537
This work presents a novel semi-supervised dictionary learning framework that updates the dictionary by online learning and is efficient in utilizing the training data. The method employs a two-stage process to train the dictionary: initial training with limited labeled data, followed by online refinement using abundant unlabeled data. We introduce an adaptive correction weight to control the influence of new unlabeled data on the dictionary update based on its consistency with the current model estimate. This approach enables efficient use of the training data set. Moreover, results in faster dictionary convergence and improves data representation accuracy, especially in scenarios with limited training data. Experimental results demonstrate significant enhancement in the classification accuracy of the proposed method compared to the state-of-the-art semi-supervised dictionary learning methods, particularly when dealing with a limited number of training samples.
This research introduces a new method for predicting electric vehicles (EVs) range that combines cloud computing with random forest regression (RFR) approaches. Predicting the range properly is now critical for user c...
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The Generalized Adaptive Weighted Recursive Least Squares (GAWRLS) dictionary learning method has shown potential for unsupervised dictionary learning. This paper advances GAWRLS by incorporating classification error ...
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ISBN:
(数字)9798331506520
ISBN:
(纸本)9798331506537
The Generalized Adaptive Weighted Recursive Least Squares (GAWRLS) dictionary learning method has shown potential for unsupervised dictionary learning. This paper advances GAWRLS by incorporating classification error as an additional cost to enable supervised learning tasks and introduces the Label Consistency for online supervised dictionary learning in classification tasks. The new method is denoted as Label Consistent Generalized Adaptive Weighted Recursive Least Squares Dictionary Learning (LC-GAWRLS). By incorporating both sparse representation error and classification error into the cost function, LC-GAWRLS enables simultaneous learning of the dictionary and classifier parameters. Particularly, to ensure label consistency, the proposed algorithm introduces a correction weight to adaptively regulate the impact of each training data during the model update, enhancing robustness against variations in training data compared to previous dictionary learning methods. Simulation results on real datasets demonstrate that LC-GAWRLS achieves higher classification accuracy compared to existing state-of-the-art supervised dictionary learning methods, particularly in scenarios with limited training samples per class.
This paper deals with the optimal control of electric and automated buses that have to follow an intercity line, where some stops are equipped with a flash-charging infrastructure to charge the batteries, while others...
This paper deals with the optimal control of electric and automated buses that have to follow an intercity line, where some stops are equipped with a flash-charging infrastructure to charge the batteries, while others are not. In order to control these buses, it is necessary to account for the traffic conditions along the roads of the bus line, and to minimize two objectives related to the deviations from the bus timetable and the lack of energy, at the end of the bus trip, with respect to a desired final energy level. The resulting optimal control problem is a multi-objective linear quadratic problem with both continuous and integer variables. In this paper, we propose and apply two methods based on lexicographic ordering aimed at determining the Pareto-optimal solutions of the control problem in twelve scenarios inspired by a real case.
While eye tracking technology has been around for several years, it has traditionally been implemented on personal computers using specific devices. Eye tracking through smartphones or tablets is much more challenging...
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This preliminary study explores developing and implementing upper-limb rehabilitation tools utilizing haptic feedback and 3D spatial recognition analysis in a virtual reality (VR) environment. The effectiveness of upp...
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A map is necessary for tasks such as path planning or localization, which are common to mobile robot navigation. However, a map may be unavailable if the environment in which a robot navigates is unknown. Creating a m...
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When designing an imaging system to perform photoacoustic-guided hysterectomy, one approach to achieve direct illumination of an imaging target is to attach optical fibers to the surgical tool. However, light blockage...
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The human brain can effortlessly imagine a 3D image from only 2D images with a little expertise and imagination, but for machines, this is not a trivial task. Because of this, reconstructing 3D images from 2D ones is ...
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