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The optical-flow aided navigation for the INS

The optical-flow aided navigation for the INS

MIPPR 2009 - Automatic Target recognition and image Analysis: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Pan, Chao Liu, Jianguo Xiao, Wei State Key Laboratory for Multispectral Information Processing Technologies Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei 430074 China

ISBN: (纸本)9780819478061

The inertial navigation system (INS) is an efficient navigation method but it can occur accumulative errors. To correct this error in the INS, this paper presents a novel optical-flow aided navigation method by studying the terrain aided navigation, which can implement the continuous error estimation of the INS by employing the extended kalman filter that regards optical-flow as its measurement parameter. Therefore, this aided method is similar to the terrain aided navigation except that the measurement parameter and equation are both derived from optical-flow instead of terrain height. Experiments with some actual aerial image sequences have proven the efficiency of this aided navigation method. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Kalman filters

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ResAsapp: An Effective Convolution to Distinguish Adjacent Pixels For Scene Text Detection 11

ResAsapp: An Effective Convolution to Distinguish Adjacent P...

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11th International Conference on Computing and pattern recognition, ICCPR 2022

作者： Weng, Kangming Du, Xia Chen, Kunze Wang, Dahan Zhu, Shunzhi School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen361024 China

ISBN: (纸本)9781450397056

The segmentation-based approach is an essential direction of scene text detection, and it can detect arbitrary or curved text, which has attracted the increasing attention of many researchers. However, extensive research has shown that the segmentation-based method will be disturbed by adjoining pixels and cannot effectively identify the text boundaries. To tackle this problem, we proposed a ResAsapp Conv based on the PSE algorithm. This convolution structure can provide different scale visual fields about the object and make it effectively recognize the boundary of texts. The method's effectiveness is validated on three benchmark datasets, CTW1500, Total-Text, and ICDAR2015 datasets. In particular, on the CTW1500 dataset, a dataset full of long curve text in all kinds of scenes, which is hard to distinguish, our network achieves an F-measure of 81.2%. © 2022 ACM.

关键词： Pixels

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Encapsulation strategies on 2D materials for field effect transistors and photodetectors

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Chinese Chemical Letters 2022年第5期33卷 2281-2290页

作者： Wenjuan Huang Yue Zhang Mengting Song Bugao Wang Huayi Hou Xiaozong Hu Xiangbai Chen Tianyou Zhai Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of TechnologyWuhan 430205China State Key Laboratory of Materials Processing and Die&Mould Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China Green Catalysis Center College of ChemistryZhengzhou UniversityZhengzhou 450001China

Two-dimensional(2D)layered materials provide a promising alternative solution for overcoming the scal-ing limits in conventional Si-based ***,practical applications of 2D materials are facing crucial bottlenecks,particularly that arising from the instability under ambient *** studies of degradation mechanisms and protecting strategies for overcoming the ambient instability of 2D materials have attracted extensive research attentions,both experimentally and *** review attempts to provide an overview on the recent progress of the encapsulation strategies for 2D *** en-capsulation strategies of mechanical transfer,polymer capping,atomic layer deposition,in-situ oxidation,and surface functionalization are systematically discussed for improving the ambient stability of 2D *** addition,the current advances in air-stable and high-performance 2D materials-based field effect transistors(FETs)and photodetectors assisted by the encapsulation strategies are ***,the future directions of encapsulation techniques of 2D materials for FETs and photodetectors applications are suggested.

关键词： Two-dimensional materials Encapsulation Degradation Stability Field effect transistors Photodetectors

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ArtDiff: Artwork Generation via Conditional Diffusion Models 23

ArtDiff: Artwork Generation via Conditional Diffusion Models

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15th International Conference on Digital image processing, ICDIP 2023

作者： Liu, Wenhui Liu, Bin Lin, Xiao Li, Bo He, Zhifen Wang, Kang School of Mathematics and Information Science Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Hangkong University Jiangxi Nanchang China Department of Supercomputing Management Jiangxi Science and Technology Infrastructure Center Jiangxi Nanchang China

ISBN: (纸本)9798400708237

Artwork Generation is an important research area of computer vision. Recently, kinds of generative models have achieved great success in natural image generation. However, artwork generation has rarely been studied due to the unfixed structure of artworks. Combined with prevailing diffusion models, we propose a simple yet effective framework, named as ArtDiff, for artwork generation. Given a name of an artist, we can generate diverse and novel artworks which reflecting the style of the artist. To the best of our knowledge, ArtDiff is the first diffusion model that generate artworks with the guidance of artist's name. Experimental results demonstrate that ArtDiff is able to recognize the artist's preference and generate artworks with reasonable structures and fine-grained details. © 2023 ACM.

关键词： Diffusion

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A flower algorithm for autonomous star pattern recognition

A flower algorithm for autonomous star pattern recognition

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作者： Gong, Jiaqi Ma, Jie Tian, Jinwen State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781563479694

An autonomous star pattern recognition algorithm is proposed herein that is effectively stable against the higher level noise than other algorithms. In simulations using an 8×8 degree field of view (FOV), the algorithm identifies the correct section of sky on 99.5% of the sensor orientations where spatial accuracy of the imaged star is 2 pixels (0.03 degree) in standard deviation and the apparent brightness deviate by 0.5 units' stellar magnitude. The achievable performance comes from the generation of the Flower-code pattern, which includes angular distances and circular angles as the characteristics of the pivot star. The angular distances are used for initial lookup table match. Moreover, the circular angles are adopted for the cyclic dynamic match between the sensor pattern and the pattern candidates from the initial match. And also, the performance is demonstrated via a comparison study on two published algorithms. Copyright © 2009 by the American Institute of Aeronautics and Astronautics, Inc.

关键词： Table lookup

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Multi-Level Kernel Machine for Scene image Classification

Multi-Level Kernel Machine for Scene Image Classification

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International Conference on Computational Intelligence and Security

作者： Junlin Hu Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

ISBN: (纸本)9781457720086

Recently, a new representation for recognizing instances and categories of scenes called spatial Principal component analysis of Census Transform histograms (PACT) has shown its excellent performance in the scene image classification task. PACT captures local structures of an image through the Census Transform (CT), meanwhile, large scale structures are captured by the strong correlation between neighboring CT values and the histogram. However, the original spatial PACT only simply concatenates all levels compact histograms together, and discards the difference between various levels. In order to improve this problem, we propose a multi-level kernel machine method, which computes a set of base kernels at each level of pyramid of PACT, and finds optimal weights for best fusing all these base kernels for scene recognition. Experiments on two popular benchmark datasets demonstrate that our proposed multi-level kernel machine method outperforms the spatial PACT on scene recognition. Besides, our method is easy to be implemented comparing with spatial PACT.

关键词： Kernel Computed tomography Transforms Computer vision Histograms Conferences Support vector machines

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Fast on-ship route planning using improved sparse A-star algorithm for UAVs

Fast on-ship route planning using improved sparse A-star alg...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Yang, Xin Ding, Mingyue Zhou, Chengping Cai, Chao Yu, Qi Shao, Shuai Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

This paper presented improved Sparse A-Star Search (SAS) algorithm to pursue a fast route planner for Unmanned Aerial Vehicles (UAVs) on-ship applications. Our approach can quickly produce 3-D trajectories composed by a set of successive navigation points from certain known initial locations to predetermined target locations. The result routes are not only ensuring collision avoidance with the environmental obstacles, but also satisfying specific routes constraints and objectives. The experiment results demonstrated the feasibility of the method, which makes our route planner be more useful in real systems. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Ships

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Path planning for UAV based on quantum-behaved particle swarm optimization

Path planning for UAV based on quantum-behaved particle swar...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Fu, Yangguang Ding, Mingyue Zhou, Chengping Cai, Chao Sun, Yangguang Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

Based on quantum-behaved particle swarm optimization (QPSO), a novel path planner for unmanned aerial vehicle (UAV) is employed to generate a safe and flyable path. The standard particle swarm optimization (PSO) and quantum-behaved particle swarm optimization (QPSO) are presented and compared through a UAV path planning application. Every particle in swarm represents a potential path in search space. For the purpose of pruning the search space, constraints are incorporated into the pre-specified cost function, which is used to evaluate whether a particle is good or not. As the system iterated, each particle is pulled toward its local attractor, which is located between the personal best position (pbest) and the global best position (gbest) based on the interaction of particles' individual searches and group's public search. For the sake of simplicity, we only consider planning the projection of path on the plane and assume threats are static instead of moving. Simulation results demonstrated the effectiveness and feasibility of the proposed approach. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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A novel algorithm for small dim target detection in distorted infrared image sequence

A novel algorithm for small dim target detection in distorte...

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MIPPR 2009 - Automatic Target recognition and image Analysis: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Qu, Xiaolei Zuo, Zhengrong Li, Xiafeng Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multispectral Information Processing Technologies Huazhong University of Science and Technology Wuhan Hubei 430074 China

ISBN: (纸本)9780819478061

A novel algorithm is proposed in this paper to detect dim moving point target with several pixels size in infrared image sequence, taken by line scan camera in high speed moving platform, with heavy background clutter and distortion. In the algorithm, the regional information of candidate points, which are extracted from the images after background suppression by spatial filter, is employed to track candidate points. After tracking candidate points, the velocity of every candidate points can be calculated easily, and false candidate points which are extracted from clutter background, can be find out by velocity classification and removed. Then, Double Hough Transform is applied on associating the remnant candidate points in multi-frame sequence to detect the target. The algorithm can get a high detection probability and reduce false alarm rate dramatically. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Hough transforms

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Global systolic array for fast computation of 3-D moment invariants

Global systolic array for fast computation of 3-D moment inv...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Liu, J.G. Chen, Shaobo Wang, Hai State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology WuHan HuBei 430074 China

ISBN: (纸本)9780819478085

The 3-D moment invariants are introduced to solve the problem of recognition of 3-D objects independent of size, position, and orientation. In this paper, based on our previous systolic array for fast computation of 3-D moment, we propose a new global systolic array for fast computation of 3-D moment invariants. The systolic sarray mostly consists of adders with area complexity O(n) and are highly regular and structurally very simple, resulting in simple hardware implementation. The method is suitable for both binary images and gray level images and is also suitable for image sequence moments. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Systolic arrays

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