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Article
A zeroing feedback gradient-based neural dynamics model for solving dynamic quadratic programming problems with linear equation constraints in finite time
Gradient-based neural dynamics (GND) models are a classical algorithm for solving optimization problems, but it has non-negligible flaws in solving dynamic problems. In this study, a novel GND model, namely th...
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Article
Geometry-based anisotropy representation learning of concepts for knowledge graph embedding
The entities in the knowledge graphs are generally categorized into concepts and instances, where each concept is used to represent the abstraction of a set of instances with common properties. Most previous K...
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Article
Modified Newton Integration Neural Algorithm for Solving Time-Varying Yang-Baxter-Like Matrix Equation
This paper intends to solve the time-varying Yang-Baxter-like matrix equation (TVYBLME), which is frequently employed in the fields of scientific computing and engineering applications. Due to its critical and...
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Chapter and Conference Paper
Learning Spatiotemporal Frequency-Transformer for Compressed Video Super-Resolution
Compressed video super-resolution (VSR) aims to restore high-resolution frames from compressed low-resolution counterparts. Most recent VSR approaches often enhance an input frame by “borrowing” relevant textu...
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Chapter and Conference Paper
Improving Dialogue Generation with Commonsense Knowledge Fusion and Selection
Knowledge-aware dialogue generation aims to generate informative and meaningful responses with external knowledge. Existing works are still insufficient to encode retrieved knowledge regardless of the dialogue...
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Article
Modified Newton integration algorithm with noise suppression for online dynamic nonlinear optimization
The solution of nonlinear optimization is usually encountered in many fields of scientific researches and engineering applications, which spawns a large number of corresponding algorithms to cope with it. Besi...
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Chapter and Conference Paper
A Proxy Node Resource Load Balancing Strategy Based on the Swift System
The internet of Things (IoT) uses wireless sensor devices to build a huge network transmission center, the data is increasing, and the data types have diverse characteristics. Such data raise a certain challen...
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Chapter and Conference Paper
A Non-autoregressive Decoding Model Based on Joint Classification for 3D Human Pose Regression
Recently, the graph convolution networks (GCN) has been widely applied in 3D human pose regression and has showed encouraging performance. One limitation of this method is that it only models the semantic corr...
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Article
Belief-peaks clustering based on fuzzy label propagation
For unsupervised learning, we propose a new clustering method which incorporates belief peaks into a linear label propagation strategy. The proposed method aims to reveal the data structure by finding out the ...
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Chapter and Conference Paper
3D Human Body Reconstruction from a Single Image
In this paper, a generative adversarial network based on SMPL model is used to reconstruct three-dimensional (3D) human mesh from a single image. The generative adversarial network consists of two parts (gener...
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Chapter and Conference Paper
On Position and Attitude Control of Flap** Wing Micro-aerial Vehicle
The flap** wing micro-air vehicle (FWMAV) is a new type of aerial vehicle which uses mechanical structure to simulate bird flight. The FWMAV possesses the characteristics of small size, light weight, high fl...
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Article
Manifold regularized multiple kernel learning with Hellinger distance
The aim of this paper is to solve the problem of unsupervised manifold regularization being used under supervised classification circumstance. This paper not only considers that the manifold information of dat...
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Chapter and Conference Paper
U-Net with Attention Mechanism for Retinal Vessel Segmentation
Retinal vessel is the only vessel which can be observed directly, retinal vessel analysis is a crucial method for the screening and diagnosis of related diseases. In this paper, we propose a retinal vessel seg...
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Article
Semi-supervised classification of multiple kernels embedding manifold information
For semi-supervised learning, we propose the Laplacian embedded multiple kernel regression model. As we incorporate the multiple kernel occasion into manifold regularization framework, the models we proposed a...
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Article
Pedestrian tracking for infrared image sequence based on trajectory manifold of spatio-temporal slice
The research of pedestrian tracking in infrared image sequences is a curial part of video surveillance. Considering the particular characteristics of the infrared image, such as low contrast, fuzzy edge and un...
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Chapter and Conference Paper
Hand Target Extraction of Thermal Trace Image Using Feature and Manifold Inspired by Coordination of Immune
In this paper, the immune mechanism is used to solve the problem of fuzzy target extraction in infrared thermal trace images. First, imitating the innate immunity, the maximum variance method was used to initi...
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Chapter and Conference Paper
Adaptive Learning Compressive Tracking Based on Kalman Filter
Object tracking has theoretical and practical application value in video surveillance, virtual reality and automatic navigation. Compressive tracking(CT) is widely used because of its advantages in accuracy a...
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Chapter and Conference Paper
An Artery/Vein Classification Method Based on Color and Vascular Structure Information
Identifying arteries and veins from fundus images plays an important role in human health census. Fundus images have the characteristics of uneven brightness, complexly staggered vessels, tiny difference betwe...
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Chapter and Conference Paper
Research and Application of Corrosion Prediction Based on GRA-SVR
Corrosion prediction is a technology of finding the corrosion law based on material corrosion data. Due to corrosion data has the characteristics of high dimensional nonlinearity, randomness and limited sizes,...
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Chapter and Conference Paper
Research on a Super-Sparse Data Generation Model for Temperature Data Map
Data visualization is an important method in data mining, and temperature data map is one of the methods of data visualization. When sample temperature points are limited, it brings the main content of the res...