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International Conference on pattern recognition

作者： Cao, Yudong Zhang, Honggang Gao, Yanyan Xu, Xiaojun Guo, Jun Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China Liaoning University of Technology Jinzhou China

ISBN: (纸本)9780769541099

In this paper, we present the fusional feature composed of Affine-SIFT, MSER and color moment invariants. The fusional feature is more robust and distinctive than a single local feature. Instead of adding three local features together simply, an efficient two-level matching strategy is devised with the fusional feature, which speeds up the establishment of the local correspondences. To remove partial false positives, an affine transformation is estimated with the weighted RANSAC which decreases iteration times. The experimental results show that our approach can achieve more accurate correspondence. We prospect to apply the fusional feature and match strategy to image retrieval in the end. © 2010 IEEE.

关键词： Image matching

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A new RCNN-RF for efficient and robust parking lot available detection 16

A new RCNN-RF for efficient and robust parking lot available...

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16th International Conference on Digital Image Processing, ICDIP 2024

作者： Zhang, Qian Ran, Yaqin Luo, Di Xu, Kaili Shi, Jilaing School of Data Science and Information Engineering GuiZhou MinZu University Guiyang550025 China Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guiyang550025 China

ISBN: (数字)9781510682917

ISBN: (纸本)9781510682900

It's very meaningful to conduct the driver to the parking space available in the parking lot clearly and accurately by computer vision and computational intelligence. While it is an extremely difficult task, because of the scene complexity in the parking lot. In this paper, a new computational intelligence technology is proposed to detect parking spaces available in the parking lot outdoor based on fusing of Region Convolution Neural Network (RCNN) and random forests (RF), and we called it as RCNN-RF. Within the RCNN-RF, a new activation function is design. And with the help of random forests, RCNN-RF overcomes scene complexity includes illumination, weather, and slight occlusion successfully. Extensive experimental results on the benchmark dataset named PKLot and the self-built dataset named GZMU-LOT outperform those of the state-of-the-art, and it shows the superiority of our proposed RCNN-RF method. © 2024 SPIE.

关键词： Random forests

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Feature Decoupled of Deep Mutual Information Maximization 2

Feature Decoupled of Deep Mutual Information Maximization

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2nd International Conference on Automation, Robotics and Computer Engineering, ICARCE 2023

作者： He, Xing Peng, Changgen Wang, Lin Tan, Weijie Wang, Zifan State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang China Guizhou Big Data Academy Guizhou University Guiyang China Guizhou Minzu University Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guiyang China Institute of Guizhou Aerospace Measuring and Testing Technology Guiyang China

ISBN: (纸本)9798350308341

In deep learning, supervised learning techniques usually require a large amount of expensive labeled data to train the network, and the feature representations extracted by the model usually mix multiple attributes, resulting in feature representations that are difficult to decouple and are non-interpretable, which restricts the application and development of deep learning techniques, and for this reason, it is particularly important to study decoupled feature representation methods for unsupervised learning. Although the Learning deep representations by mutual information estimation and maximization (DIM) method achieves excellent results in unsupervised learning, the feature representations learned by the DIM method still suffer from the problem of difficult decoupling. decoupling problem. To address this problem, we minimize the mutual information between the intermediate layer feature representations learned by the hidden layer of the encoder during the encoder training process, so that the features learned by each filter are as uncorrelated as possible, thus realizing feature decoupling, and our method is called FP-DIM. Finally, the effectiveness of the FP-DIM method is verified on the CIFAR-10, STL-10, and Fashion-MNIST datasets. The experiments show that our proposed FP-DIM method is more significant for the learned decouplable middle layer feature representation. Finally, we also propose a reflection of future research for the FP-DIM method, aiming to provide a research idea and direction for solving unsupervised interpretable machine learning and to lay a solid theoretical and application foundation for machine learning fields such as image classification and migration learning. © 2023 IEEE.

关键词： Unsupervised learning

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Study of the 6.x nm short wavelength radiation spectra of laser-produced erbium plasmas for BEUV lithography

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Plasma Science and Technology 2023年第6期25卷 41-51页

作者：吴涛王倩陈柳安陆培祥 Hubei Key Laboratory of Optical Information and Pattern Recognition School of Optical Information and Energy EngineeringWuhan Institute of TechnologyWuhan 430205People's Republic of China Guangdong Intelligent Robotics Institute Dongguan 523808People's Republic of China

Beyond extreme ultraviolet(BEUV)radiation with a wavelength of 6.x nm for lithography is responsible for reducing the source wavelength to enable continued miniaturization of semiconductor *** this work,the Required BEUV light at 6.x nm wavelength was generated in dense and hot Nd:YAG laser-produced Er *** spectral contributions from the 4p–4d and 4d–4f transitions of singly,doubly and triply excited states of Er XXIV–Er XXXII in the BEUV band were calculated using Cowan and the Flexible Atomic *** was also found that the radiative transitions between multiply excited states dominate the narrow wavelength window around 6.x *** the assumption of collisional radiative equilibrium of the laser-produced Er plasmas,the relative ion abundance in the experiment was *** the Boltzmann quantum state energy level distribution and Gram–Charlier fitting function of unresolved transition arrays(UTAs),the synthetic spectrum around 6.x nm was finally obtained and compared with the experimental *** spatio-temporal distributions of electron density and electron temperature were calculated based on radiation hydrodynamic simulation in order to identify the contributions of various ionic states to the UTAs arising from the Er plasmas near 6.x nm.

关键词： laser-produced plasmas unresolved transition array collisional radiative equilibrium

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intelligent Parking Big Data Cloud Platform Algorithm Research and Application 6

Intelligent Parking Big Data Cloud Platform Algorithm Resear...

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6th International Conference on Computer Information Science and Application Technology, CISAT 2023

作者： Yan, Xiaobo Zou, Xue Cai, Shan Wang, Lin Key Laboratory of Pattern Recognition and Intelligent System of Guizhou Province Guizhou Minzu University Guiyang China College of Date Science and Information Engineering Guizhou Minzu University Guiyang China

ISBN: (纸本)9781510668546

With the rapid development of the domestic economy and the increasing living standards of the people, the ownership of private cars has increased explosively. Currently, urban traffic congestion and parking difficulty have gradually become a hot topic of research from all walks of life. Parking difficulty is mainly reflected on the following aspects: first, the existing parking spaces in cities are not effectively utilized;The second reason is that drivers cannot grasp relevant information about parking spaces near the ground in real time. This article conducts in-depth research on the issue of parking difficulty. Based on the existing security monitoring systems in parking lots, real-time detection of parking spaces status is conducted based on computer vision, machine learning, and other methods. By building a comprehensive, synthesize, and multi-dimensional parking resources dynamic sensing system, a smart parking big data cloud platform is constructed to achieve the effect of intelligent indoor parking lots management. © 2023 SPIE.

关键词： Machine learning

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Object classification via PCANet and color constancy model 4

Object classification via PCANet and color constancy model

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4th International Conference on Advanced Design and Manufacturing Engineering, ADME 2014

作者： Hu, De Kun Zhang, L. Zhao, Wei Dong Yan, Tao Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province Chengdu University Chengdu China

ISBN: (纸本)9783038352570

In order to classify the objects in nature images, a model with color constancy and principle component analysis network (PCANet) is proposed. The new color constancy model imitates the functional properties of the HVS from the retina to the double-opponent cells in V1. PCANet can be designed and learned extremely, which comprises only the very basic data processing components: cascaded principal component analysis (PCA), binary hashing, and block-wise histograms. At last, a SVM is trained to classify the object in the image. The results of experiments demonstrate the potential of the model for object classification in wild color images. © (2014) Trans Tech Publications, Switzerland.

关键词： Object recognition

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recognition of facial expression via kernel PCA network 3

Recognition of facial expression via kernel PCA network

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3rd International Conference on Information Technology and Management Innovation, ICITMI 2014

作者： Hu, De Kun Ye, An Sheng Li, Li Zhang, Li Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province Chengdu University Chengdu China

ISBN: (纸本)9783038352396

In this work, a kernel principle component analysis network (KPCANet) is proposed for classification of the facial expression in unconstrained images, which comprises only the very basic data processing components: cascaded kernel principal component analysis (KPCA), binary hashing, and block-wise histograms. In the proposed model, KPCA is employed to learn multistage filter banks. It is followed by simple binary hashing and block histograms for indexing and pooling. For comparison and better understanding, We have tested these basic networks extensively on many benchmark visual datasets(such as the JAFFE [13] database, the CMU AMP face expression database, a part of the Extended Cohn-Kanade (CK+) database), The results demonstrate the potential of the KPCANet serving as a simple but highly competitive baseline for facial expression recognition. © 2014 Trans Tech Publications, Switzerland.

关键词： Database systems

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AN EFFICIENT DUPLICATE IMAGE DETECTION METHOD BASED ON AFFINE-SIFT FEATURE

AN EFFICIENT DUPLICATE IMAGE DETECTION METHOD BASED ON AFFIN...

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2010 3rd IEEE International Conference on Broadband Network & Multimedia Technology(2010年第三届IEEE宽带网络与多媒体国际会议 IC-BNMT 2010)

作者： Yudong Cao Honggang Zhang Yanyan Gao Jun Guo Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunica Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunica Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunica

In this paper, we present a novel scheme to tackle the task of near-duplicate image detection. Given two input images, the algorithm based on the refined similarity measure can judge rightly whether two input image are duplicate images or not. The two images are represented with local feature (i.e, Affine-SIFT) in bag of features model. The Affine-SIFT can undergo larger affine distortions than Hessian-Affine and MSER (Maximally Stable Extremal Region). The refined similarity measure exploits the spatial information between two images. The algorithm is demonstrated on some image pairs with scale change, viewpoint change, blur, noise and spatial deformation. The experimental results show that proposed algorithm is more effective than other state-of-the-art duplicate image detection algorithm.

关键词： duplicate detection image matching Affine-SIFT

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MambaMIM: Pre-training Mamba with state space token interpolation and its application to medical image segmentation

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Medical Image Analysis 2025年 103卷 103606页

作者： Tang, Fenghe Nian, Bingkun Li, Yingtai Jiang, Zihang Yang, Jie Liu, Wei Zhou, S. Kevin School of Biomedical Engineering Division of Life Sciences and Medicine University of Science and Technology of China Anhui Hefei230026 China Suzhou Institute for Advanced Research University of Science and Technology of China Jiangsu Suzhou215123 China Suzhou Institute for Advanced Research USTC Jiangsu Suzhou215123 China Department of Automation Shanghai Jiao Tong University Shanghai China Institute of Image Processing and Pattern Recognition Shanghai China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Jiangsu Provincial Key Laboratory of Multimodal Digital Twin Technology Jiangsu Suzhou215123 China State Key Laboratory of Precision and Intelligent Chemistry University of Science and Technology of China Anhui Hefei230026 China

Recently, the state space model Mamba has demonstrated efficient long-sequence modeling capabilities, particularly for addressing long-sequence visual tasks in 3D medical imaging. However, existing generative self-supervised learning methods have not yet fully unleashed Mamba's potential for handling long-range dependencies because they overlook the inherent causal properties of state space sequences in masked modeling. To address this challenge, we propose a general-purpose pre-training framework called MambaMIM, a masked image modeling method based on a novel TOKen-Interpolation strategy (TOKI) for the selective structure state space sequence, which learns causal relationships of state space within the masked sequence. Further, MambaMIM introduces a bottom-up 3D hybrid masking strategy to maintain a masking consistency across different architectures and can be used on any single or hybrid Mamba architecture to enhance its multi-scale and long-range representation capability. We pre-train MambaMIM on a large-scale dataset of 6.8K CT scans and evaluate its performance across eight public medical segmentation benchmarks. Extensive downstream experiments reveal the feasibility and advancement of using Mamba for medical image pre-training. In particular, when we apply the MambaMIM to a customized architecture that hybridizes MedNeXt and Vision Mamba, we consistently obtain the state-of-the-art segmentation performance. The code is available at: https://***/FengheTan9/MambaMIM. © 2025

关键词： Image segmentation

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Natural image matting based on image inpainting 2

Natural image matting based on image inpainting

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2nd International Conference on Computer Graphics, Image and Virtualization, ICCGIV 2022

作者： Zhang, Yuan Tan, Mian Zhou, Zhulian Yang, Yuan Liang, Yihui Feng, Fujian Guizhou Minzu University Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guiyang550025 China University of Electronic Science and Technology China School of Computer Science Zhongshan528400 China

ISBN: (纸本)9781665492508

Deep image matting is a hot problem with applications in computer vision and image processing. It has been widely used in image composition, film production and video editing etc. The current matting method based on image inpainting uses a deep neural network to inpaint the foreground target and background region to further improve the accuracy of alpha matte. However, when the trimap contains large unknown regions, the excessive inpainting of foreground and background produce a lot of redundant information, which leads to a degradation of alpha matte quality. Therefore, to address this issue, a natural image matting method based on image inpainting is designed. This method involves the refinement process for trimap, which improves the quality of the trimap, enlarges the foreground and background regions providing additional information for image matting. Extensive experimental results on the composition-1k dataset demonstrate that the presented method provide high-quality alpha mattes not only in the case that the trimap contains small unknown regions, but also in the case that the trimap contains large unknown regions. © 2022 IEEE.

关键词： Deep neural networks

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