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基于注意力感知和语义感知的RGB-D室内图像语义分割算法 CSCD
期刊论文 | 2021 , 44 (02) , 275-291 | 计算机学报
CNKI被引次数: 3
摘要&关键词 引用

摘要 :

近年来,全卷积神经网络有效提升了语义分割任务的准确率.然而,由于室内环境的复杂性,室内场景语义分割仍然是一个具有挑战性的问题.随着深度传感器的出现,人们开始考虑利用深度信息提升语义分割效果.以往的研究大多简单地使用等权值的拼接或求和操作来融合RGB特征和深度特征,未能充分利用RGB特征与深度特征之间的互补信息.本文提出一种基于注意力感知和语义感知的网络模型ASNet(Attention-aware and Semantic-aware Network).通过引入注意力感知多模态融合模块和语义感知多模态融合模块,有效地融合多层次的RGB特征和深度特征.其中,在注意力感知多模态融合模块中,本文设计...

关键词 :

深度学习 深度学习 RGB-D语义分割 RGB-D语义分割 卷积神经网络 卷积神经网络 注意力模型 注意力模型 多模态融合 多模态融合

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GB/T 7714 段立娟 , 孙启超 , 乔元华 et al. 基于注意力感知和语义感知的RGB-D室内图像语义分割算法 [J]. | 计算机学报 , 2021 , 44 (02) : 275-291 .
MLA 段立娟 et al. "基于注意力感知和语义感知的RGB-D室内图像语义分割算法" . | 计算机学报 44 . 02 (2021) : 275-291 .
APA 段立娟 , 孙启超 , 乔元华 , 陈军成 , 崔国勤 . 基于注意力感知和语义感知的RGB-D室内图像语义分割算法 . | 计算机学报 , 2021 , 44 (02) , 275-291 .
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Bifurcation analysis and global dynamics in a predator-prey system of Leslie type with an increasing functional response SCIE
期刊论文 | 2021 , 455 | ECOLOGICAL MODELLING
WoS核心集被引次数: 3
摘要&关键词 引用

摘要 :

The dynamical behaviors of a Leslie type predator-prey system are explored when the functional response is increasing for both predator and prey. Qualitative and quantitative analysis methods based on stability theory, bifurcation theory and numerical simulation are adopted. It is showed that the system is dissipative and permanent, and its solutions are bounded. Global stability of the unique positive equilibrium is investigated by constructing Dulac function and applying Poincare-Bendixson theorem. The bifurcation behaviors are further explored and the number of limit cycles is determined. By calculating the first Lyapunov number and the first two focus values, it is proved that the positive equilibrium is not a center but a weak focus of multiplicity at most two, so the system undergoes Hopf bifurcation and Bautin bifurcation. The normal form of Bautin bifurcation is also obtained by introducing the complex system. Moreover, numerical simulations are run to demonstrate the validity of theoretical results.

关键词 :

Bautin bifurcation Bautin bifurcation Global stability Global stability Hopf bifurcation Hopf bifurcation Limit cycle Limit cycle Predator-prey system Predator-prey system

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GB/T 7714 Shang, Zuchong , Qiao, Yuanhua , Duan, Lijuan et al. Bifurcation analysis and global dynamics in a predator-prey system of Leslie type with an increasing functional response [J]. | ECOLOGICAL MODELLING , 2021 , 455 .
MLA Shang, Zuchong et al. "Bifurcation analysis and global dynamics in a predator-prey system of Leslie type with an increasing functional response" . | ECOLOGICAL MODELLING 455 (2021) .
APA Shang, Zuchong , Qiao, Yuanhua , Duan, Lijuan , Miao, Jun . Bifurcation analysis and global dynamics in a predator-prey system of Leslie type with an increasing functional response . | ECOLOGICAL MODELLING , 2021 , 455 .
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基于注意力感知和语义感知的RGB-D室内图像语义分割算法 CQVIP
期刊论文 | 2021 , 44 (2) , 275-291 | 段立娟
摘要&关键词 引用

摘要 :

基于注意力感知和语义感知的RGB-D室内图像语义分割算法

关键词 :

RGB-D语义分割 RGB-D语义分割 卷积神经网络 卷积神经网络 多模态融合 多模态融合 注意力模型 注意力模型 深度学习 深度学习

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GB/T 7714 段立娟 , 孙启超 , 乔元华 et al. 基于注意力感知和语义感知的RGB-D室内图像语义分割算法 [J]. | 段立娟 , 2021 , 44 (2) : 275-291 .
MLA 段立娟 et al. "基于注意力感知和语义感知的RGB-D室内图像语义分割算法" . | 段立娟 44 . 2 (2021) : 275-291 .
APA 段立娟 , 孙启超 , 乔元华 , 陈军成 , 崔国勤 , 计算机学报 . 基于注意力感知和语义感知的RGB-D室内图像语义分割算法 . | 段立娟 , 2021 , 44 (2) , 275-291 .
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Periodic dynamics of multidirectional associative neural networks with discontinuous activation functions and mixed time delays SCIE
期刊论文 | 2021 , 31 (10) , 4570-4588 | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
WoS核心集被引次数: 3
摘要&关键词 引用

摘要 :

Multidirectional associative memory neural networks (MAMNNs) are constructed to simulate the many-to-many association, and they are applied widely in many fields. It is important to explore the global stability of the periodic solution of MAMNNs. In this paper, MAMNNs with discontinuous activation functions and mixed time-varying delays are considered. Firstly, we investigate the conditions for the existence of the periodic solution by using the Mawhin-like coincidence theorem, and a special connecting weight matrix is constructed to prove the existence of the periodic solution. Secondly, the uniqueness and global exponential stability of the periodic solution are explored for the non-self-connected system by introducing a Lipschitz-like condition. Finally, numerical simulations are given to illustrate the effectiveness of our main results.

关键词 :

discontinuous activation functions discontinuous activation functions global exponential stability global exponential stability mixed time&#8208 mixed time&#8208 multidirectional associative memory neural networks multidirectional associative memory neural networks periodic solution periodic solution varying delays varying delays

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GB/T 7714 Zhang, Yan , Qiao, Yuanhua , Duan, Lijuan et al. Periodic dynamics of multidirectional associative neural networks with discontinuous activation functions and mixed time delays [J]. | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL , 2021 , 31 (10) : 4570-4588 .
MLA Zhang, Yan et al. "Periodic dynamics of multidirectional associative neural networks with discontinuous activation functions and mixed time delays" . | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 31 . 10 (2021) : 4570-4588 .
APA Zhang, Yan , Qiao, Yuanhua , Duan, Lijuan , Miao, Jun , Zhang, Jiajia . Periodic dynamics of multidirectional associative neural networks with discontinuous activation functions and mixed time delays . | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL , 2021 , 31 (10) , 4570-4588 .
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Novel methods to global Mittag-Leffler stability of delayed fractional-order quaternion-valued neural networks SCIE
期刊论文 | 2021 , 142 , 500-508 | NEURAL NETWORKS
WoS核心集被引次数: 12
摘要&关键词 引用

摘要 :

In this paper, a type of fractional-order quaternion-valued neural networks (FOQVNNs) with leakage and time-varying delays is established to simulate real-world situations, and the global Mittag-Leffler stability of the system is investigated by using the non-decomposition method. First, to avoid decomposing the system into two complex-valued systems or four real-valued systems, a new sign function for quaternion numbers is introduced based on the ones for real and complex numbers. And two novel lemmas for quaternion-valued sign function and Caputo fractional derivative are established in quaternion domain, which are used to investigate the stability of FOQVNNs. Second, a concise and flexible quaternion-valued state feedback controller is directly designed and a novel 1-norm Lyapunov function composed of the absolute values of real and imaginary parts is established. Then, based on the designed quaternion-valued state feedback controller and the proposed lemmas, some sufficient conditions are given to ensure the global Mittag-Leffler stability of the system. Finally, a numerical simulation is given to verify the theoretical results. (C) 2021 Elsevier Ltd. All rights reserved.

关键词 :

Fractional-order Fractional-order Leakage delay Leakage delay Mittag-Leffler stability Mittag-Leffler stability Quaternion-valued neural networks Quaternion-valued neural networks Time-varying delay Time-varying delay

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GB/T 7714 Yan, Hongyun , Qiao, Yuanhua , Duan, Lijuan et al. Novel methods to global Mittag-Leffler stability of delayed fractional-order quaternion-valued neural networks [J]. | NEURAL NETWORKS , 2021 , 142 : 500-508 .
MLA Yan, Hongyun et al. "Novel methods to global Mittag-Leffler stability of delayed fractional-order quaternion-valued neural networks" . | NEURAL NETWORKS 142 (2021) : 500-508 .
APA Yan, Hongyun , Qiao, Yuanhua , Duan, Lijuan , Miao, Jun . Novel methods to global Mittag-Leffler stability of delayed fractional-order quaternion-valued neural networks . | NEURAL NETWORKS , 2021 , 142 , 500-508 .
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An automated method with anchor-free detection and U-shaped segmentation for nuclei instance segmentation EI
会议论文 | 2021 | 2nd ACM International Conference on Multimedia in Asia, MMAsia 2020
摘要&关键词 引用

摘要 :

Nuclei segmentation plays an important role in cancer diagnosis. Automated methods for digital pathology become popular due to the developments of deep learning and neural networks. However, this task still faces challenges. Most of current techniques cannot be applied directly because of the clustered state and the large number of nuclei in images. Moreover, anchor-based methods for object detection lead a huge amount of calculation, which is even worse on pathological images with a large target density. To address these issues, we propose a novel network with an anchor-free detection and a U-shaped segmentation. An altered feature enhancement module is attached to improve the performance in dense target detection. Meanwhile, the U-Shaped structure in segmentation block ensures the aggregation of features in different dimensions generated from the backbone network. We evaluate our work on a Multi-Organ Nuclei Segmentation dataset from MICCAI 2018 challenge. In comparisons with others, our proposed method achieves state-of-the-art performance. © 2021 ACM.

关键词 :

Chemical detection Chemical detection Deep learning Deep learning Deep neural networks Deep neural networks Object detection Object detection Object recognition Object recognition

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GB/T 7714 Feng, Xuan , Duan, Lijuan , Chen, Jie . An automated method with anchor-free detection and U-shaped segmentation for nuclei instance segmentation [C] . 2021 .
MLA Feng, Xuan et al. "An automated method with anchor-free detection and U-shaped segmentation for nuclei instance segmentation" . (2021) .
APA Feng, Xuan , Duan, Lijuan , Chen, Jie . An automated method with anchor-free detection and U-shaped segmentation for nuclei instance segmentation . (2021) .
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A deep multimodal feature learning network for RGB-D salient object detection EI
期刊论文 | 2021 , 92 | Computers and Electrical Engineering
摘要&关键词 引用

摘要 :

In this paper, we propose a deep multimodal feature learning (DMFL) network for RGB-D salient object detection. The color and depth features are firstly extracted from low level to high level feature using CNN. Then the features at the high layer are shared and concatenated to construct joint feature representation of multi-modalities. The fused features are embedded to a high dimension metric space to express the salient and non-salient parts. And also a new objective function, consisting of cross-entropy and metric loss, is proposed to optimize the model. Both pixel and attribute level discriminative features are learned for semantical grouping to detect the salient objects. Experimental results show that the proposed model achieves promising performance and has about 1% to 2% improvement to conventional methods. © 2021 Elsevier Ltd

关键词 :

Deep learning Deep learning Feature extraction Feature extraction Object detection Object detection Object recognition Object recognition Set theory Set theory Topology Topology

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GB/T 7714 Liang, Fangfang , Duan, Lijuan , Ma, Wei et al. A deep multimodal feature learning network for RGB-D salient object detection [J]. | Computers and Electrical Engineering , 2021 , 92 .
MLA Liang, Fangfang et al. "A deep multimodal feature learning network for RGB-D salient object detection" . | Computers and Electrical Engineering 92 (2021) .
APA Liang, Fangfang , Duan, Lijuan , Ma, Wei , Qiao, Yuanhua , Miao, Jun . A deep multimodal feature learning network for RGB-D salient object detection . | Computers and Electrical Engineering , 2021 , 92 .
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Bifurcation analysis in a predator-prey system with an increasing functional response and constant-yield prey harvesting SCIE
期刊论文 | 2021 , 190 , 976-1002 | MATHEMATICS AND COMPUTERS IN SIMULATION
WoS核心集被引次数: 17
摘要&关键词 引用

摘要 :

In this paper, a Gause type predator-prey system with constant-yield prey harvesting and monotone ascending functional response is proposed and investigated. We focus on the influence of the harvesting rate on the predator-prey system. First, equilibria corresponding to different situations are investigated, as well as the stability analysis. Then bifurcations are explored at nonhyperbolic equilibria, and we give the conditions for the occurrence of two saddle-node bifurcations by analyzing the emergence, coincidence and annihilation of equilibria. We calculate the Lyapunov number and focal values to determine the stability and the quantity of limit cycles generated by supercritical, subcritical and degenerate Hopf bifurcations. Furthermore, the system is unfolded to explore the repelling and attracting Bogdanov-Takens bifurcations by perturbing two bifurcation parameters near the cusp. It is shown that there exists one limit cycle, or one homoclinic loop, or two limit cycles for different parameter values. Therefore, the system is susceptible to both the constant-yield prey harvesting and initial values of the species. Finally, we run numerical simulations to verify the theoretical analysis. (C) 2021 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.

关键词 :

Bogdanov-Takens bifurcation Bogdanov-Takens bifurcation Degenerate Hopf bifurcation Degenerate Hopf bifurcation Harvesting Harvesting Limit cycle Limit cycle Predator-prey system Predator-prey system

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GB/T 7714 Shang, Zuchong , Qiao, Yuanhua , Duan, Lijuan et al. Bifurcation analysis in a predator-prey system with an increasing functional response and constant-yield prey harvesting [J]. | MATHEMATICS AND COMPUTERS IN SIMULATION , 2021 , 190 : 976-1002 .
MLA Shang, Zuchong et al. "Bifurcation analysis in a predator-prey system with an increasing functional response and constant-yield prey harvesting" . | MATHEMATICS AND COMPUTERS IN SIMULATION 190 (2021) : 976-1002 .
APA Shang, Zuchong , Qiao, Yuanhua , Duan, Lijuan , Miao, Jun . Bifurcation analysis in a predator-prey system with an increasing functional response and constant-yield prey harvesting . | MATHEMATICS AND COMPUTERS IN SIMULATION , 2021 , 190 , 976-1002 .
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Context-aware network for RGB-D salient object detection EI
期刊论文 | 2021 , 111 | Pattern Recognition
摘要&关键词 引用

摘要 :

Convolutional neural networks (CNNs) have shown unprecedented success in object representation and detection. Nevertheless, CNNs lack the capability to model context dependencies among objects, which are crucial for salient object detection. As the long short-term memory (LSTM) is advantageous in propagating information, in this paper, we propose two variant LSTM units for the exploration of contextual dependencies. By incorporating these units, we present a context-aware network (CAN) to detect salient objects in RGB-D images. The proposed model consists of three components: feature extraction, context fusion of multiple modalities and context-dependent deconvolution. The first component is responsible for extracting hierarchical features in color and depth images using CNNs, respectively. The second component fuses high-level features by a variant LSTM to model multi-modal spatial dependencies in contexts. The third component, embedded with another variant LSTM, models local hierarchical context dependencies of the fused features at multi-scales. Experimental results on two public benchmark datasets show that the proposed CAN can achieve state-of-the-art performance for RGB-D stereoscopic salient object detection. © 2020

关键词 :

Benchmarking Benchmarking Convolutional neural networks Convolutional neural networks Long short-term memory Long short-term memory Object detection Object detection Object recognition Object recognition Stereo image processing Stereo image processing

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GB/T 7714 Liang, Fangfang , Duan, Lijuan , Ma, Wei et al. Context-aware network for RGB-D salient object detection [J]. | Pattern Recognition , 2021 , 111 .
MLA Liang, Fangfang et al. "Context-aware network for RGB-D salient object detection" . | Pattern Recognition 111 (2021) .
APA Liang, Fangfang , Duan, Lijuan , Ma, Wei , Qiao, Yuanhua , Miao, Jun , Ye, Qixiang . Context-aware network for RGB-D salient object detection . | Pattern Recognition , 2021 , 111 .
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Joint Multisource Saliency and Exemplar Mechanism for Weakly Supervised Video Object Segmentation SCIE
期刊论文 | 2021 , 30 , 8155-8169 | IEEE TRANSACTIONS ON IMAGE PROCESSING
WoS核心集被引次数: 5
摘要&关键词 引用

摘要 :

Weakly supervised video object segmentation (WSVOS) is a vital yet challenging task in which the aim is to segment pixel-level masks with only category labels. Existing methods still have certain limitations, e.g., difficulty in comprehending appropriate spatiotemporal knowledge and an inability to explore common semantic information with category labels. To overcome these challenges, we formulate a novel framework by integrating multisource saliency and incorporating an exemplar mechanism for WSVOS. Specifically, we propose a multisource saliency module to comprehend spatiotemporal knowledge by integrating spatial and temporal saliency as bottom-up cues, which can effectively eliminate disruptions due to confusing regions and identify attractive regions. Moreover, to our knowledge, we make the first attempt to incorporate an exemplar mechanism into WSVOS by proposing an adaptive exemplar module to process top-down cues, which can provide reliable guidance for co-occurring objects in intraclass videos and identify attentive regions. Our framework, which comprises the two aforementioned modules, offers a new perspective on directly constructing the correspondence between bottom-up cues and top-down cues when ground-truth information for the reference frames is lacking. Comprehensive experiments demonstrate that the proposed framework achieves state-of-the-art performance.

关键词 :

Annotations Annotations exemplar mechanism exemplar mechanism Feature extraction Feature extraction Motion segmentation Motion segmentation Object segmentation Object segmentation Spatiotemporal phenomena Spatiotemporal phenomena spatiotemporal saliency spatiotemporal saliency Task analysis Task analysis Training Training video object segmentation video object segmentation Weakly supervised learning Weakly supervised learning

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GB/T 7714 En, Qing , Duan, Lijuan , Zhang, Zhaoxiang . Joint Multisource Saliency and Exemplar Mechanism for Weakly Supervised Video Object Segmentation [J]. | IEEE TRANSACTIONS ON IMAGE PROCESSING , 2021 , 30 : 8155-8169 .
MLA En, Qing et al. "Joint Multisource Saliency and Exemplar Mechanism for Weakly Supervised Video Object Segmentation" . | IEEE TRANSACTIONS ON IMAGE PROCESSING 30 (2021) : 8155-8169 .
APA En, Qing , Duan, Lijuan , Zhang, Zhaoxiang . Joint Multisource Saliency and Exemplar Mechanism for Weakly Supervised Video Object Segmentation . | IEEE TRANSACTIONS ON IMAGE PROCESSING , 2021 , 30 , 8155-8169 .
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