Recently, the character-word lattice structure has been proved to be effective for Chinese named entity recognition (NER) by incorporating the word information. However, one hand, since the lattice structure is dynami...
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An important issue in cancer genomics is the identification of driver genes. It is significant for the discovery of key biomarkers and the development of effective personalized therapies. In this paper, a computated m...
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Preserving details and avoiding high computational costs are the two main challenges for the High-Resolution Salient Object Detection (HRSOD) task. In this paper, we propose a two-stage HRSOD model from the perspectiv...
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Preserving details and avoiding high computational costs are the two main challenges for the High-Resolution Salient Object Detection (HRSOD) task. In this paper, we propose a two-stage HRSOD model from the perspective of evolution and succession, including an evolution stage with Low-resolution Location Model (LrLM) and a succession stage with High-resolution Refinement Model (HrRM). The evolution stage achieves detail-preserving salient objects localization on the low-resolution image through the evolution mechanisms on supervision and feature;the succession stage utilizes the shallow high-resolution features to complement and enhance the features inherited from the first stage in a lightweight manner and generate the final high-resolution saliency prediction. Besides, a new metric named Boundary-Detail-aware Mean Absolute Error (MAEBD) is designed to evaluate the ability to detect details in high-resolution scenes. Extensive experiments on five datasets demonstrate that our network achieves superior performance at real-time speed (49 FPS) compared to state-of-the-art methods. Our code is publicly available at: https://***/rmcong/ESNet_ICML24. Copyright 2024 by the author(s)
The solvable problem of adaptive inverse optimal stabilization in probability is discussed, and control laws of global asymptotic stability in probability and adaptive inverse optimal stabilization in probability are ...
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The solvable problem of adaptive inverse optimal stabilization in probability is discussed, and control laws of global asymptotic stability in probability and adaptive inverse optimal stabilization in probability are developed for output-feedback stochastic nonlinear continuous systems with additive standard Wiener noises and constant unknown parameters by using It(o)'s differentiation rule and adaptive backstepping algorithms. The adaptive control law and the parameter update laws can be obtained at same time by this design scheme.
Continuous subgraph matching (CSM) is a critical task for analyzing dynamic graphs and has a wide range of applications, such as merchant fraud detection, cyber-attack hunting, and rumor detection. Although many effic...
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Motion is one of the basic physiological functions of human beings. However, many brain diseases such as stroke may cause different degrees of motor dysfunctions for patients. As a commonly used rehabilitation method,...
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In this paper, we first propose a Zhang neural dynamics (ZND) model for the generalized Sinkhorn scaling of time-varying matrix. Specifically, by using the dimensional reduction technique, a continuous-time ZND model ...
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Since 2014, Zhang time discretization (ZTD, also termed Zhang et al. discretization) formulas have been put forward as a new method for time discretization by Zhang et al. Originally, ZTD formulas were used to obtain ...
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Salient object detection(SOD)in RGB and depth images has attracted increasing research *** RGB-D SOD models usually adopt fusion strategies to learn a shared representation from RGB and depth modalities,while few meth...
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Salient object detection(SOD)in RGB and depth images has attracted increasing research *** RGB-D SOD models usually adopt fusion strategies to learn a shared representation from RGB and depth modalities,while few methods explicitly consider how to preserve modality-specific *** this study,we propose a novel framework,the specificity-preserving network(SPNet),which improves SOD performance by exploring both the shared information and modality-specific ***,we use two modality-specific networks and a shared learning network to generate individual and shared saliency prediction *** effectively fuse cross-modal features in the shared learning network,we propose a cross-enhanced integration module(CIM)and propagate the fused feature to the next layer to integrate cross-level ***,to capture rich complementary multi-modal information to boost SOD performance,we use a multi-modal feature aggregation(MFA)module to integrate the modalityspecific features from each individual decoder into the shared *** using skip connections between encoder and decoder layers,hierarchical features can be fully *** experiments demonstrate that our SPNet outperforms cutting-edge approaches on six popular RGB-D SOD and three camouflaged object detection *** project is publicly available at https://***/taozh2017/SPNet.
As a significant and basic robotic sub-topic, the problem of optimal MPC (motion planning & control) of ordinarily redundant manipulator widely exists in many fields, such as industry and daily-life applications. ...
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