Disassembly lines are the most effective way to address large-scale value recovery from end-of-life (EOL) products. Disassembly line balancing (DLB) greatly affects the economics and throughput of EOL product processing. Complete disassembly is general…
Text classification has been widely explored in natural language processing. In this article, we propose a novel adaptive dense ensemble model (AdaDEM) for text classification, which includes local ensemble stage (LES) and global dense ensemble stage (…
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Multiview subspace clustering (MVSC) is a recently emerging technique that aims to discover the underlying subspace in multiview data and thereby cluster the data based on the learned subspace. Though quite a few MVSC methods have been proposed in rece…
Diagnosing the fault as early as possible is significant to guarantee the safety and reliability of the high-speed train. Incipient fault always makes the monitored signals deviate from their normal values, which may lead to serious consequences gradua…
This article proposes the problem of joint state estimation and correlation identification for data fusion with unknown and time-varying correlation under the Bayesian learning framework. The considered data correlation is represented by the randomly w…
In the past several years, it has become apparent that the effectiveness of Pareto-dominance-based multiobjective evolutionary algorithms deteriorates progressively as the number of objectives in the problem, given by $M$ , grows. This is mainly due t…
This article proposes a Riemannian adaptive optimization algorithm to optimize the parameters of deep neural networks. The algorithm is an extension of both AMSGrad in Euclidean space and RAMSGrad on a Riemannian manifold. The algorithm helps to resolv…
This article demonstrates that nonmaximum suppression (NMS), which is commonly used in object detection (OD) tasks to filter redundant detection results, is no longer secure. Considering that NMS has been an integral part of OD systems, thwarting the f…