检索结果-内蒙古大学图书馆

International Conference on Space Information Technology

作者： Lu, Li Shi, Baochang Tian, Jinwen Liu, Jian State Education Commission Key Lab for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei 430074 China Inst. for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei 430074 China Department of Mathematics Huazhong University of Science and Technology Wuhan Hubei 430074 China

Walsh-Haar function system that was first intruoduced by us is a new kind of function systems, and has a good global/local property. This function system is called Walsh ordering function system since its generation kernel functions belong to Walsh ordering Walsh function system. We worked out a recursive property of the matrix WHKRm+1 corresponding to the first KR m+1 Walsh-Haar functions in Walsh-Haar function system, and we also proved that Walsh-Haar function system is perfect and orthogonal similar to Walsh function system and Haar function system. Thus, discrete Walsh-Haar transformation (DW-HT) is an orthogonal transformation that can be widely used in signal processing. In this paper, using the recursive property of the matrix WHKRm+1 and the fast algorithm of discrete Walsh transformation (DWT) in Walsh ordering, we have designed a fast algorithm of Walsh ordering DW-HT based on the bisection technique. The idea and method used in this paper can be used for designing fast algorithms of other ordering DW-HTs and other discrete orthogonal transformations.

关键词： Mathematical transformations

来源：评论

学校读者我要写书评

暂无评论

Multiple objects segmentation based on Maximum-likelihood Estimation and Optimum Entropy-distribution(MLE-OED)

Proceedings - International Conference on Pattern Recognitio...

引用

Proceedings - International Conference on pattern recognition 2002年第1期16卷 707-710页

作者： Jun, Xie Tsui, H.T. Deshen, Xia Image Processing and Computer Vision Lab Department of Electronic Engineering Chinese University of Hong Kong Hong Kong Pattern Recognition Lab Department of Computer Science Nanjing University of Sci. and Tech. China

A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss function proposed to implement image segmentation based on the image's local spatial information and global intensity distribution properties . The loss function consists of two terms: a local content fitting term, which optimizes the entropy distribution, and a global statistical fitting term, which maximizes the likelihood of the parameters for the given data. The proposed segmentation method was validated by simulated and real examples. Its performance in the experiments is better than those of two popular methods. © 2002 IEEE.

关键词： Object recognition

来源：评论

学校读者我要写书评

暂无评论

Data consistent artifact reduction for limited angle tomography with deep learning prior

arXiv

引用

arXiv 2019年

作者： Huang, Yixing Preuhs, Alexander Lauritsch, Günter Manhart, Michael Huang, Xiaolin Maier, Andreas Pattern Recognition Lab Friedrich-Alexander-Universitt Erlangen-Nrnberg Erlangen91058 Germany Siemens Healthcare GmbH Forchheim91301 Germany Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai200240 China Erlangen91058 Germany

Robustness of deep learning methods for limited angle tomography is challenged by two major factors: a) due to insufficient training data the network may not generalize well to unseen data;b) deep learning methods are sensitive to noise. Thus, generating reconstructed images directly from a neural network appears inadequate. We propose to constrain the reconstructed images to be consistent with the measured projection data, while the unmeasured information is complemented by learning based methods. For this purpose, a data consistent artifact reduction (DCAR) method is introduced: First, a prior image is generated from an initial limited angle reconstruction via deep learning as a substitute for missing information. Afterwards, a conventional iterative reconstruction algorithm is applied, integrating the data consistency in the measured angular range and the prior information in the missing angular range. This ensures data integrity in the measured area, while inaccuracies incorporated by the deep learning prior lie only in areas where no information is acquired. The proposed DCAR method achieves significant image quality improvement: for 120° cone-beam limited angle tomography more than 10% RMSE reduction in noise-free case and more than 24% RMSE reduction in noisy case compared with a state-of-the-art U-Net based method. Copyright © 2019, The Authors. All rights reserved.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

The INTERSPEECH 2010 paralinguistic challenge

The INTERSPEECH 2010 paralinguistic challenge

引用

作者： Schuller, Björn Steidl, Stefan Batliner, Anton Burkhardt, Felix Devillers, Laurence Müller, Christian Narayanan, Shrikanth CNRS-LIMSI Spoken Language Processing Group Orsay France FAU Erlangen-Nuremberg Pattern Recognition Lab. Germany Deutsche Telekom AG Laboratories Berlin Germany Saarbrücken Germany University of Southern California SAIL Los Angeles CA United States

Most paralinguistic analysis tasks are lacking agreed-upon evaluation procedures and comparability, in contrast to more 'traditional' disciplines in speech analysis. The INTERSPEECH 2010 Paralinguistic Challenge shall help overcome the usually low compatibility of results, by addressing three selected sub-challenges. In the Age Sub-Challenge, the age of speakers has to be determined in four groups. In the Gender Sub-Challenge, a three-class classification task has to be solved and finally, the Affect Sub-Challenge asks for speakers' interest in ordinal representation. This paper introduces the conditions, the Challenge corpora "aGender" and "TUM AVIC" and standard feature sets that may be used. Further, baseline results are given. © 2010 ISCA.

关键词： Linguistics

来源：评论

学校读者我要写书评

暂无评论

Leveraging Open Knowledge for Advancing Task Expertise in Large Language Models

arXiv

引用

arXiv 2024年

作者： Yang, Yuncheng Qin, Yulei Wu, Tong Xu, Zihan Li, Gang Guo, Pengcheng Shao, Hang Shi, Yuchen Li, Ke Sun, Xing Yang, Jie Gu, Yun Institute of Image Processing and Pattern Recognition Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China Tencent YouTu Lab Shanghai200233 China

The cultivation of expertise for large language models (LLMs) to solve tasks of specific areas often requires special-purpose tuning with calibrated behaviors on the expected stable outputs. To avoid huge cost brought by manual preparation of instruction datasets and training resources up to hundreds of hours, the exploitation of open knowledge including a wealth of low rank adaptation (LoRA) models and instruction datasets serves as a good starting point. However, existing methods on model and data selection focus on the performance of general-purpose capabilities while neglecting the knowledge gap exposed in domain-specific deployment. In the present study, we propose to bridge such gap by introducing few human-annotated samples (i.e., K-shot) for advancing task expertise of LLMs with open knowledge. Specifically, we develop an efficient and scalab.e pipeline to cost-efficiently produce task experts where K-shot data intervene in selecting the most promising expert candidates and the task-relevant instructions. A mixture-of-expert (MoE) system is built to make the best use of individual-yet-complementary knowledge between multiple experts. We unveil the two keys to the success of a MoE system, 1) the abidance by K-shot, and 2) the insistence on diversity. For the former, we ensure that models that truly possess problem-solving abilities on K-shot are selected rather than those blind guessers. Besides, during data selection, instructions that share task-relevant contexts with K-shot are prioritized. For the latter, we highlight the diversity of constituting experts and that of the fine-tuning instructions throughout the model and data selection process. Extensive experimental results confirm the superiority of our approach over existing methods on utilization of open knowledge across various tasks. Our codes will be availab.e at https://***/Yaphabates/Rocket. © 2024, CC BY.

关键词： Pipeline codes

来源：评论

学校读者我要写书评

暂无评论

Multi-homed VPN architecture based on extended SOCKS+TLS protocols

引用

Journal of Shanghai Jiaotong University (Science) 2005年第3期10 E卷 250-255页

作者： Zhang, Bao-Liang Hu, Han-Ping Chen, Xiang State Education Ministry Key Lab. of Image Information and Intelligent Control Inst. of Pattern Recognition and Artificial Intelligence Huazhong Univ. of Science and Technology Wuhan 430074 China

A multi-homed VPN architecture based on extended SOCKSv5 and TLS was proposed. The architecture employs a dynamic connection mechanism for multiple proxies in the end system, in which the security-demanded transmission connections can switch smoothly among the multiple proxies by maintaining a coherent connection context. The mechanism is transparent to application programs and can support the building of VPN. With the cooperation of some other security components, the mechanism guarantees the resource availab.lity and reliability of the end system against some attacks to the specific ports or hosts.

关键词： Virtual reality

来源：评论

学校读者我要写书评

暂无评论

Multifeature distance map based detection of small infrared targets with low contrast in image sequences

Multifeature distance map based detection of small infrared ...

引用

International Conference on Space Information Technology

作者： Wang, Zhicheng Gao, Chenqiang Tian, Jinwen Liu, Jian Chen, Xiangping State Education Commission Key Lab for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei 430074 China Inst. for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei 430074 China Electronic and Engineering Department Huazhong University of Science and Technology Wuhan Hubei 430074 China

Target detection techniques play an important role in automatic target recognition (ATR) systems because overall ATR performance depends closely on detection results. In this paper, a novel method for fusion detection of infrared weak targets based on multifeature distance map (MFDM) in image sequences is proposed. As for small weak targets, there are many features, such as local entropy, average gradient strength. These features depict the characteristics of small infrared targets and can be extracted. Multifeature-based fusion techniques are applied to detect such weak targets. The problem of detecting small targets is converted to search peak values in specified feature space where multifeature vectors space (MFVS) is considered. Distance map (DM) can be derived according to feature vectors and target detection is performed in DM. In order to accumulate energy of targets deeply and suppress background and clutters to a great extent, five distance maps obtained by corresponding five consecutive frames are utilized to fuse with average weight, which results in the fact that the contrast between targets and background including clutters are enlarged and that the feature peaks of targets are obvious different from background and clutters. After these steps, a contrast segmentation method is used to extract targets from complicated background on the fused DM. Actual infrared image sequences in background of sea and sky are applied to validate the proposed approach. Experimental results demonstrate the robustness of the proposed method with high performance.

关键词： Automatic target recognition

来源：评论

学校读者我要写书评

暂无评论

Scale-space anisotropic total variation for limited angle tomography

arXiv

引用

arXiv 2017年

作者： Huang, Yixing Taubmann, Oliver Huang, Xiaolin Haase, Viktor Lauritsch, Guenter Maier, Andreas Pattern Recognition Lab Friedrich-Alexander-University Erlangen-Nuremberg Erlangen Germany Pattern Recognition Lab FriedrichAlexander-University Erlangen-Nuremberg Erlangen Germany Erlangen Germany Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Siemens Healthcare GmbH Forchheim Germany Department of Radiology University of Utah Salt Lake CityUT United States

This paper addresses streak reduction in limited angle tomography. Although the iterative reweighted total variation (wTV) algorithm reduces small streaks well, it is rather inept at eliminating large ones since total variation (TV) regularization is scale-dependent and may regard these streaks as homogeneous areas. Hence, the main purpose of this paper is to reduce streak artifacts at various scales. We propose the scale-space anisotropic total variation (ssaTV) algorithm in two different implementations. The first implementation (ssaTV-1) utilizes an anisotropic gradient-like operator which uses 2 · s neighboring pixels along the streaks' normal direction at each scale s. The second implementation (ssaTV-2) makes use of anisotropic down-sampling and up-sampling operations, similarly oriented along the streaks' normal direction, to apply TV regularization at various scales. Experiments on numerical and clinical data demonstrate that both ssaTV algorithms reduce streak artifacts more effectively and efficiently than wTV, particularly when using multiple scales. Copyright © 2017, The Authors. All rights reserved.

关键词： Anisotropy

来源：评论

学校读者我要写书评

暂无评论

On integration of vision modules

On integration of vision modules

引用

IEEE Computer Society Conference on Computer Vision and pattern recognition Workshops (CVPRW)

作者： Pankanti Jain Tuceryan Pattern Recognition and Image Proc. Lab. Michigan State University East Lansing MI USA European Computer-Industry Research Centre Munchen Germany

Individual cues from visual modules are fallible and often ambiguous. As a result, only integrated vision systems can be expected to give a reliable performance in practice. The design of such systems is challenging since each vision module works under different and possibly conflicting sets of assumptions. We have proposed and implemented a multiresolution system which integrates perceptual grouping, segmentation, stereo, shape from shading, and line lab.lling modules. The output of the integrated system is shown to be relatively insensitive to the constraints imposed by the individual modules.< >

关键词： Machine vision image segmentation Stereo vision

来源：评论

学校读者我要写书评

暂无评论

Fast Template Matching with Partial Skipping Using Sub-template

Fast Template Matching with Partial Skipping Using Sub-templ...

引用

International Conference on Audio, Language and image processing

作者： Qiao Zhang Huijie Gao Zhen Kang State Key Lab. of Multi-spectral Information Processing Technology Institute for Pattern Recognition and Artificial Intelligence School of Mathematic & Computer Science Wuhan Polytechnic University

ISBN: (纸本)9781467301732

This paper presents a new fast template matching method with partial skipping using sub-template. In this method, we use sub-template to search point by point in the current searched window, and compare every SAD with threshold, if some SAD exceeds the threshold, set the new threshold equal to this SAD value and this point is one potential optimization location, when all points in the current window are compared, we will get a minimum value and a optimization location, then skip the other points whose SAD is not the minimum value. In other words, the searching step is that template size subtracts the sub-template size, and we set the next threshold equal to the current optimization SAD value, we update the threshold and the optimal point until the end of the searched image like this, then will find the global minimum points and its SAD value. Experimental results show that the proposed method is near one hundred times faster than the conventional template match method.

关键词： Computational efficiency Prediction algorithms Search problems Accuracy Correlation Signal processing algorithms pattern recognition

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：