Stroke and heart attack,which could be led by a kind of cerebrovascular and cardiovascular disease named as atherosclerosis,would seriously cause human morbidity and *** is important for the early stage diagnosis and ...
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Stroke and heart attack,which could be led by a kind of cerebrovascular and cardiovascular disease named as atherosclerosis,would seriously cause human morbidity and *** is important for the early stage diagnosis and monitoring medical intervention of the *** stenosis is a classical atherosclerotic lesion with vessel wall narrowing down and accumulating plaques *** carotid artery of intima-media thickness(IMT)is a key indicator to the *** the development of computer assisted diagnosis technology,the imaging techniques,segmentation algorithms,measurement methods,and evaluation tools have made considerable *** imaging,being real-time,economic,reliable,and safe,now seems to become a standard in vascular assessment methodology especially for the measurement of *** review firstly attempts to discuss the clinical relevance of measurements in clinical practice at first,and then followed by the challenges that one has to face when approaching the segmentation of ultrasound ***,the commonly used methods for the IMT segmentation and measurement are ***,discussion and evaluation of different segmentation techniques are *** overview of summary and future perspectives is given finally.
Spectrum mapping reflects the strength of brain electrical activity in different frequency *** current study analyzes changes in electroencephalography(EEG) after spinal cord injury(SCI) on the basis of spectrum *** s...
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ISBN:
(纸本)9781467358873
Spectrum mapping reflects the strength of brain electrical activity in different frequency *** current study analyzes changes in electroencephalography(EEG) after spinal cord injury(SCI) on the basis of spectrum *** spectrum mappings of SCI patients and normal subjects,the fact that beta rhythm dominated in brain electrical activity during walking period was *** addition,the proportion of delta wave increased and slightly exceeded that of beta wave after spinal cord injury and power values in delta band of SCI patients performed greater than that of normal subjects.
The global asymptotic stability of fuzzy cellular neural networks with unbounded time-varying delays and Lipschitz continuous activation functions is investigated in this brief. Based on the concept of comparison, som...
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This paper studies a novel distributed optimization problem that aims to minimize the sum of the non-convex objective functionals of the multi-agent network under privacy protection, which means that the local objecti...
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This paper studies a novel distributed optimization problem that aims to minimize the sum of the non-convex objective functionals of the multi-agent network under privacy protection, which means that the local objective of each agent is unknown to others. The above problem involves complexity simultaneously in the time and space aspects. Yet existing works about distributed optimization mainly consider privacy protection in the space aspect where the decision variable is a vector with finite dimensions. In contrast, when the time aspect is considered in this paper, the decision variable is a continuous function concerning time. Hence, the minimization of the overall functional belongs to the calculus of variations. Traditional works usually aim to seek the optimal decision function. Due to privacy protection and non-convexity, the Euler-Lagrange equation of the proposed problem is a complicated partial differential ***, we seek the optimal decision derivative function rather than the decision function. This manner can be regarded as seeking the control input for an optimal control problem, for which we propose a centralized reinforcement learning(RL) framework. In the space aspect, we further present a distributed reinforcement learning framework to deal with the impact of privacy protection. Finally, rigorous theoretical analysis and simulation validate the effectiveness of our framework.
Human salience of pedestrians images is distinctive and has been shown importantly in person re-identification (or pedestrians identification) problem. Thus, how to obtain the salient area of pedestrian images is impo...
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Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization *** on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from the perspec...
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Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization *** on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from the perspectives of network update strategy,initialization method,and parameter *** paper compares the performance of the proposed algorithms with the performance of existing SOM network algorithms on the TSP and compares them with several heuristic *** show that compared with existing SOM networks,the improved SOM network proposed in this paper improves the convergence rate and algorithm *** with iterated local search and heuristic algorithms,the improved SOM net-work algorithms proposed in this paper have the advantage of fast calculation speed on medium-scale TSP.
Visual localization is a crucial component in the application of mobile robot and autonomous *** retrieval is an efficient and effective technique in image-based localization *** to the drastic variability of environm...
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Visual localization is a crucial component in the application of mobile robot and autonomous *** retrieval is an efficient and effective technique in image-based localization *** to the drastic variability of environmental conditions,e.g.,illumination changes,retrievalbased visual localization is severely affected and becomes a challenging *** this work,a general architecture is first formulated probabilistically to extract domain-invariant features through multi-domain image ***,a novel gradientweighted similarity activation mapping loss(Grad-SAM)is incorporated for finer localization with high *** also propose a new adaptive triplet loss to boost the contrastive learning of the embedding in a self-supervised *** final coarse-to-fine image retrieval pipeline is implemented as the sequential combination of models with and without Grad-SAM *** experiments have been conducted to validate the effectiveness of the proposed approach on the CMU-Seasons *** strong generalization ability of our approach is verified with the RobotCar dataset using models pre-trained on urban parts of the CMU-Seasons *** performance is on par with or even outperforms the state-of-the-art image-based localization baselines in medium or high precision,especially under challenging environments with illumination variance,vegetation,and night-time ***,real-site experiments have been conducted to validate the efficiency and effectiveness of the coarse-to-fine strategy for localization.
The tracking of maneuvering targets in radar networking scenarios is studied in this *** the interacting multiple model algorithm and the expected-mode augmentation algorithm,the fixed base model set leads to a mismat...
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The tracking of maneuvering targets in radar networking scenarios is studied in this *** the interacting multiple model algorithm and the expected-mode augmentation algorithm,the fixed base model set leads to a mismatch between the model set and the target motion mode,which causes the reduction on tracking *** adaptive grid-expected-mode augmentation variable structure multiple model algorithm is *** adaptive grid algorithm based on the turning model is extended to the two-dimensional pattern space to realize the self-adaptation of the model ***,combining with the unscented information filtering,and by interacting the measurement information of neighboring radars and iterating information matrix with consistency strategy,a distributed target tracking algorithm based on the posterior information of the information matrix is *** the problem of filtering divergence while target is leaving radar surveillance area,a k-coverage algorithm based on particle swarm optimization is applied to plan the radar motion trajectory for achieving filtering convergence.
A new model-based human body tracking framework with learning-based theory is introduced in this *** propose a variable structure multiple model (VSMM) framework to address challenging problems such as uncertainty of ...
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A new model-based human body tracking framework with learning-based theory is introduced in this *** propose a variable structure multiple model (VSMM) framework to address challenging problems such as uncertainty of motion styles,imprecise detection of feature points,and ambiguity of joint *** human joint points are detected automatically and the undetected points are estimated with Kalman *** motion models are learned from motion capture data using a ridge regression *** model set that covers the total motion set is designed on the basis of topological and compatibility relationships,while the VSMM algorithm is used to estimate quaternion vectors of joint *** using real image sequences and simulation videos demonstrate the high efficiency of our proposed human tracking framework.
Visual servoing has been around for decades, but the time delay is still one of the most troublesome problems to achieve maneuvering target *** circumvent the problem, in this paper, the Kalman filter is employed to e...
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Visual servoing has been around for decades, but the time delay is still one of the most troublesome problems to achieve maneuvering target *** circumvent the problem, in this paper, the Kalman filter is employed to estimate future position of the maneuvering *** order to introduce the Kalman filter, the accurate time delays, which include the processing lag and the motion lag, need to be ***, the delays of the visual control servoing systems are discussed, and a generic timing model for the system are ***, we present a current statistical model for maneuvering *** adaptive Kalman filter, which is evolved from the Kalman filter, is put forward based on the current statistical *** results show that the modified adaptive filter can improve the ability of maneuvering target tracking.
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