Support vector machine(SVM)is a binary classifier widely used in machine ***,neglecting the latent data structure in previous SVM can limit the performance of SVM and its *** address this issue,the authors propose a n...
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Support vector machine(SVM)is a binary classifier widely used in machine ***,neglecting the latent data structure in previous SVM can limit the performance of SVM and its *** address this issue,the authors propose a novel SVM with discriminative low-rank embedding(LRSVM)that finds a discriminative latent low-rank subspace more suitable for SVM *** extension models of LRSVM are introduced by imposing different orthogonality constraints to prevent computational inaccuracies.A detailed derivation of the authors’iterative algorithms are given that is essentially for solving the SVM on the low-rank ***,some theorems and properties of the proposed models are presented by the *** is worth mentioning that the subproblems of the proposed algorithms are equivalent to the standard or the weighted linear discriminant analysis(LDA)*** indicates that the projection subspaces obtained by the authors’algorithms are more suitable for SVM classification compared to those from the LDA *** convergence analysis for the authors proposed algorithms are also ***,the authors conduct experiments on various machine learning data sets to evaluate the *** experiment results show that the authors’algorithms perform significantly better than other algorithms,which indicates their superior abilities on classification tasks.
With the advancement of neural networks, diverse methods for neural Granger causality have emerged, which demonstrate proficiency in handling complex data, and nonlinear ***, the existing framework of neural Granger c...
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With the advancement of neural networks, diverse methods for neural Granger causality have emerged, which demonstrate proficiency in handling complex data, and nonlinear ***, the existing framework of neural Granger causality has several *** requires the construction of separate predictive models for each target variable, and the relationship depends on the sparsity on the weights of the first layer, resulting in challenges in effectively modeling complex relationships between variables as well as unsatisfied estimation accuracy of Granger ***, most of them cannot grasp full-time Granger *** address these drawbacks, we propose a Jacobian Regularizer-based Neural Granger Causality (JRNGC) approach, a straightforward yet highly effective method for learning multivariate summary Granger causality and full-time Granger causality by constructing a single model for all target ***, our method eliminates the sparsity constraints of weights by leveraging an input-output Jacobian matrix regularizer, which can be subsequently represented as the weighted causal matrix in the post-hoc *** experiments show that our proposed approach achieves competitive performance with the state-of-the-art methods for learning summary Granger causality and full-time Granger causality while maintaining lower model complexity and high scalability. Copyright 2024 by the author(s)
Three-dimensional(3D)lidar has been widely used in various *** MEMS scanning system is one of its most important components,while the limitation of scanning angle is the main obstacle to improve the demerit for its ap...
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Three-dimensional(3D)lidar has been widely used in various *** MEMS scanning system is one of its most important components,while the limitation of scanning angle is the main obstacle to improve the demerit for its application in various *** this paper,a folded large field of view scanning optical system is *** structure and parameters of the system are determined by theoretical derivation of ray *** optical design software Zemax is used to design the *** optimization,the final structure performs well in collimation and beam *** results show that the scan angle can be expanded from±5°to±26.5°,and finally the parallel light scanning is *** spot diagram at a distance of 100 mm from the exit surface shows that the maximum radius of the spot is 0.506 mm with a uniformly distributed *** maximum radius of the spot at 100 m is 19 cm,and the diffusion angle is less than 2 *** energy concentration in the spot range is greater than 90%with a high system energy concentration,and the parallelism is *** design overcomes the shortcoming of the small mechanical scanning angle of the MEMS lidar,and has good performance in collimation and beam *** provides a design method for large-scale application of MEMS lidar.
作者:
Goraksha, RahulBongale, ArunkumarSayyad, SameerKumar, Satish
Symbiosis Institute of Technology Department of Robotics and Automation Pune412115 India
Symbiosis Centre for Applied Artificial Intelligence Department of Robotics and Automation Pune412115 India
There is a rising scarcity of healthcare professionals to meet the demand of taking care of aged people. Social robots are becoming more and more popular because of the benefits they provide;during the pandemic, in pa...
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To improve transportation capacity,dual overhead crane systems(DOCSs)are playing an increasingly important role in the transportation of large/heavy cargos and ***,when trying to deal with the control problem,current ...
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To improve transportation capacity,dual overhead crane systems(DOCSs)are playing an increasingly important role in the transportation of large/heavy cargos and ***,when trying to deal with the control problem,current methods fail to fully consider such factors as external disturbances,input dead zones,parameter uncertainties,and other unmodeled dynamics that DOCSs usually suffer *** a result,dramatic degradation is caused in the control performance,which badly hinders the practical applications of *** by this fact,this paper designs a neural network-based adaptive sliding mode control(SMC)method for DOCS to solve the aforementioned issues,which achieves satisfactory control performance for both actuated and underactuated state variables,even in the presence of matched and mismatched *** asymptotic stability of the desired equilibrium point is proved with rigorous Lyapunov-based ***,extensive hardware experimental results are collected to verify the efficiency and robustness of the proposed method.
LiDAR-based 3D object detection is widely used in high-level autonomous driving schemes. However, the cumbersome modules in most 3D detectors lead to substantial computational overhead. Despite knowledge distillation ...
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In this work, the use of a single sparse Optical Phased Array (OPA) to achieve arbitrary multi-beams forming and steering is studied and demonstrated. This approach can be efficient and cost-effective for multiple-use...
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We present the approaches and contributions of the winning team NimbRo@Home at the RoboCup@Home 2024 competition in the Open Platform League held in Eindhoven, NL. Further, we describe our hardware setup and give an o...
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Tactile perception is crucial for detecting contact and identifying the attributes associated with it. In this research, we demonstrate that the mechanical properties of objects may be inferred by employing data-drive...
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In recent years, there has been a growing demand for remote sensing image semantic segmentation in various applications. The key to semantic segmentation lies in the ability to globally comprehend the input image. Whi...
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