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FLP: a feature-based method for log parsing

ELECTRONICS LETTERS 2018年第23期54卷 1334-1335页

作者： Zhong, Ya Guo, Yuanbo Liu, Chunhui Zhengzhou Inst Informat Sci & Technol 62 Sci Ave Zhengzhou Henan Peoples R China State Key Lab Math Engn & Adv Comp 62 Sci Ave Zhengzhou Henan Peoples R China

A feature-based log parsing method is presented for extracting log events from unstructured free-text logs. It is a data-driven log analytic solution with no training data needed and suitable for various types of log parsing tasks. Experiments show that the proposed method can achieve higher accuracy and lower time complexity in large-scale log data than existing log parsing methods.

关键词： feature extraction computational complexity grammars text analysis log parsing tasks log parsing methods feature-based method feature-based log parsing data-driven log analytic solution log event extraction unstructured free-text logs time complexity FLP

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A Fusion Algorithm of Visual Odometry based on feature-based method and Direct method

A Fusion Algorithm of Visual Odometry Based on Feature-based...

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Chinese Automation Congress (CAC)

作者： Feng, Jinglun Zhang, Chengjin Sun, Bo Song, Yong Shandong Univ Sch Mech Weihai Shandong Peoples R China Robooster Intelligent Technol Co Ltd Suzhou Sino Germany Suzhou Jiangsu Peoples R China

ISBN: (纸本)9781538635247

A method that optimizes visual odometry, especially using visual odometry in the scene with absence of features is proposed in this paper. First, in order to estimate the pose of camera when the effect of using feature-based method is not good enough, direct method is implemented as the solution. Second, comparing with traditional visual odometry method, this method takes the environment restriction into consideration. On the one hand, if enough feature points are detected in a frame, feature-based method is to be used;on the other hand, direct method is used in the scene of missing features so that the accuracy of pose estimation could be guaranteed and improved. Finally, the feasibility of this method is proven by a number of experiments conducted on the experiment platform.

关键词： Visual odometry restricted environment direct method feature-based method

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An Improved feature-based method for Fall Detection

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TEHNICKI VJESNIK-TECHNICAL GAZETTE 2019年第5期26卷 1363-1368页

作者： Yao, Leiyue Yang, Wei Huang, Wei Nanchang Univ Sch Informat Engn Nanchang 330031 Jiangxi Peoples R China Jiangxi Univ Technol Ctr Collaborat & Innovat Nanchang 330098 Jiangxi Peoples R China

Aiming at improving the efficiency and accuracy of fall detection, this paper fuses traditional feature-based methods and Support Vector Machine (SVM). The proposed method provides two major improvements. Firstly, the classic features were adopted and together with machine learning technology form an improved and efficient fall detection method. Secondly, the definition of a threshold which needs massive experiments was now learned by the program itself. Compared with the current popular end-to-end deep learning methods, the improved feature-based method fusing machine learning technology shows great advantages in time efficiency because of the significant reduction of the input parameters. Additionally, with the help of SVM, the thresholds need no manual definition, which saves a lot of time and makes it more precise. Our approach is evaluated on a public dataset, TST fall detection dataset v2. The results show that our approach achieves an accuracy of 93.56%, which is better than other typical methods. Furthermore, the approach can be used in real-time video surveillance because of its time efficiency and robustness.

关键词： computer vision fall detection feature-based method handcrafted feature Support Vector Machine (SVM)

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Integrated design of single-phase flow cooling channel structure and functionality for 3D chips

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INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER 2025年 240卷

作者： Zhao, Xi Zhao, Zeyu Lu, Sheng Zhao, Yang Ma, Ying Zhou, Mingdong Chongqing Univ Posts & Telecommun Sch Adv Mfg Engn 2 Chong Wen Rd Chongqing Chongqing Peoples R China Shanghai Jiao Tong Univ State Key Lab Mech Syst & Vibrat Shanghai Key Lab Digital Manufacture Thin walled S 800 Dong Chuan Rd Shanghai 200240 Peoples R China

3D chip structure is an effective way to improve integration density of electronic components per unit area. However, the stacking of electronic components in space will further exacerbate the heat dissipation problem. Adding cooling channels in the inter-layer of the 3D chip structure is an effective method to solve this problem. How to design cooling channels while considering the influence of 3D chip structural features is an urgent problem to be solved. Through-silicon via (TSV) is a special structure that connects the various layers in 3D chip. Due to design requirements, the length and size of TSV may vary, resulting indifferent amounts of heat generation. It also affects the arrangement of inter-layer cooling channels. Therefore, TSV are crucial for thermal management of 3D chips. In this work, a topology optimization method for single-phase flow cooling channel of 3D chips, which taking into account the influence of TSV, is proposed. A topology description method based on structural features is proposed to accurately describe the structural features of TSV. Combining the TSV feature-based topology description method with an efficient Darcy flow model, a finite element construction of the physical field model of inter-layer cooling channels is carried out. The parameters and strategies of the optimization algorithm were discussed through case studies of pin fin structure design, providing reference for designers. By optimizing and simulating the cooling channel structure of a certain 3D chip, the feasibility of the proposed method in this study is demonstrated.

关键词： 3D chip Through-silicon vias Cooling channels Topology optimization feature-based method Single phase flow

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Minimum Variance method to Obtain the Best Shot in Video for Face Recognition

Minimum Variance Method to Obtain the Best Shot in Video for...

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3rd International Conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Ohzeki, Kazuo Aoyama, Ryota Hirakawa, Yutaka Shibaura Inst Technol Grad Sch Engn & Sci Koutou Ku 3-7-5 Toyosu Tokyo 108 Japan

ISBN: (纸本)9788360810668

This paper describes a face recognition algorithm using feature points of face parts, which is classified as a feature-based method. As recognition performance depends on the combination of adopted feature points, we utilize all reliable feature points effectively. From moving video input, well-conditioned face images with a frontal direction and without facial expression are extracted. To select such well-conditioned images, an iteratively minimizing variance method is used with variable input face images. This iteration drastically brings convergence to the minimum variance of 1 for a quarter to an eighth of all data, which means 3.75-7.5 Hz by frequency on average. Also, the maximum interval, which is the worst case, between the two values with minimum deviation is about 0.8 seconds for the tested feature point sample.

关键词： face recognition feature extraction image classification video signal processing face recognition algorithm feature points feature-based method frequency 3.75 Hz to 7.5 Hz minimum variance method moving video input variable input face images Electronic mail Face Face recognition feature extraction Lighting Three-dimensional displays Yttrium

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Face recognition: A study in information fusion using fuzzy integral

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PATTERN RECOGNITION LETTERS 2005年第6期26卷 719-733页

作者： Kwak, KC Pedrycz, W Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2G7 Canada Chungbuk Natl Univ Dept Elect & Elect Engn Cheongju 361763 South Korea Polish Acad Sci Syst Res Inst PL-01447 Warsaw Poland

We study two approaches to fuzzy information fusion for face recognition involving aggregation of local and global face information and a wavelet decomposition approach. The former is concerned with a fuzzy information fusion involving both feature-based (e.g., eye, nose, and mouth) and template-based (global face) approaches to face recognition. The latter is associated with fuzzy information fusion based on four subimages (that is approximation, horizontal, vertical, and diagonal detailed images) using wavelet decomposition method. Making use of these two approaches, we design classifiers based on the well-known fisherface method. We demonstrate that the proposed method comes with better performance when compared with other template-based techniques and shows substantial insensitivity to large variation in light direction and facial expression. The fusion of the individual classifiers is realized by means of the Choquet fuzzy integral. The experimental results produced for FERET face database with 600 frontal face images corresponding to 200 subjects quantifies the performance of the classifier and contrast it with some other approaches existing in the literature. (c) 2004 Elsevier B.V. All rights reserved.

关键词： face recognition fuzzy information fusion feature-based method template-based method wavelet decomposition fisherfaces choquet fuzzy integral

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A coding-guided holistic-based palmprint recognition approach

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MULTIMEDIA TOOLS AND APPLICATIONS 2017年第6期76卷 7731-7747页

作者： Tabejamaat, Mohsen Mousavi, Abdolmajid Lorestan Univ Dept Elect Engn Fac Engn Khorramabad Iran

In the past few years, the need for accuracy and robustness against luminosity variations has drawn a considerable share of the palmprint research toward coding-based approaches. However, on the downside coding-based approaches require a high computational cost. On the contrary, while holistic-based palmprint recognition methods are easy to implement and have low computational burden, they usually do not result in a highly desirable accuracy. As a result, more recently hybridization of the holistic-based and coding-based methods has gained a boost. These hybridization schemes take advantages of both holistic and coding information to achieve a better performance. However, their computational burden due to incorporating the coding approach is still much heavier than the holistic methods. In this paper, we propose a new hybridization scheme based on Anisotropic Filter (AF) coding and the two-phase test sample representation (TPTSR) for the palmprint identification. In our scheme, the coding-based method is only applied on a super narrowed gallery in order to measure the classification confidence for a given test sample. Then, we apply our Guided Holistic (GH)-based method for classifying the test sample if the holistic-based algorithm is not sufficiently confident. Experimental results demonstrate the efficiency of our method in enhancing both the complexity cost and the accuracy of the results.

关键词： Palmprint recognition feature-based method Holistic-based method Coding-based method

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feature-based topology optimization for channel cooling structure

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STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2023年第3期66卷 1-16页

作者： Zhao, Xi Sun, Wei Lu, Sheng Zhou, Tianyu Zheng, Taixiong Zhao, Yang Chongqing Univ Posts & Telecomunicat Sch Adv Mfg 2 Chong Wen Rd Chongqing 400065 Peoples R China

Channel cooling structures are widely used in heat generating products and tools. A popular combination has been designing using the topology optimization method and manufacturing by an advanced method, such as 3D printing. Considering the heat sink design with its thermal mechanical effects, a feature-based cooling channel topology optimization design method is given. The presented method is adopted to accurately describe the topological parameters in the cooling channel structure. To address the phenomenon of mixing between different phases and avoid the parameter continuation tuning process by using the feature-based method, a phase-mixing constraint is proposed. To improve the computational efficiency, an equivalent flow field model fit to low and high Reynold's number is proposed. The shape feature parameters are discussed in more detail. Furthermore, a hot stamping tool is taken as an example, in which the topology optimization design of the cooling channel structure is carried out and discussed.

关键词： feature-based method Topology optimization Geometric constraint Channel cooling

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A visual servoing system with feature prediction using a motion observer

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ELECTRICAL ENGINEERING IN JAPAN 2003年第1期145卷 67-73页

作者： Saruta, K Fujimoto, H Hori, Y Univ Tokyo Tokyo Japan Nagaoka Univ Technol Nagaoka Niigata 94021 Japan

A visual servo is an eye-in-hand robot system that directly uses real-time visual information for control. This paper proposes a novel visual servoing system with motion observer (MOB)-based feature prediction. The position of the target object cannot be observed directly. The motion observer is designed as a minimum-order observer and is useful for high-performance servoing. The effectiveness of the proposed method is shown by simulations and experiments. (C) 2003 Wiley Periodicals, Inc.

关键词： visual servo feature-based method motion estimation minimum order observer motion observer (MOB)

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Region-based Object Recognition by Color Segmentation Using a Simplified PCNN

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2015年第8期26卷 1682-1697页

作者： Chen, Yuli Ma, Yide Kim, Dong Hwan Park, Sung-Kee Shaanxi Normal Univ Minist Educ Key Lab Modern Teaching Technol Xian 710119 Peoples R China Shaanxi Normal Univ Sch Comp Sci Xian 710119 Peoples R China Lanzhou Univ Sch Informat Sci & Engn Lanzhou 730000 Peoples R China Korea Inst Sci & Technol Ctr Bion Biomed Res Inst Seoul 136791 South Korea

In this paper, we propose a region-based object recognition (RBOR) method to identify objects from complex real-world scenes. First, the proposed method performs color image segmentation by a simplified pulse-coupled neural network (SPCNN) for the object model image and test image, and then conducts a region-based matching between them. Hence, we name it as RBOR with SPCNN (SPCNN-RBOR). Hereinto, the values of SPCNN parameters are automatically set by our previously proposed method in terms of each object model. In order to reduce various light intensity effects and take advantage of SPCNN high resolution on low intensities for achieving optimized color segmentation, a transformation integrating normalized Red Green Blue (RGB) with opponent color spaces is introduced. A novel image segmentation strategy is suggested to group the pixels firing synchronously throughout all the transformed channels of an image. based on the segmentation results, a series of adaptive thresholds, which is adjustable according to the specific object model is employed to remove outlier region blobs, form potential clusters, and refine the clusters in test images. The proposed SPCNN-RBOR method overcomes the drawback of feature-based methods that inevitably includes background information into local invariant feature descriptors when keypoints locate near object boundaries. A large number of experiments have proved that the proposed SPCNN-RBOR method is robust for diverse complex variations, even under partial occlusion and highly cluttered environments. In addition, the SPCNN-RBOR method works well in not only identifying textured objects, but also in less-textured ones, which significantly outperforms the current feature-based methods.

关键词： feature-based method image segmentation object recognition region-based matching simplified pulse-coupled neural network (SPCNN)

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