检索结果-内蒙古大学图书馆

7th International conference on Hybrid Intelligent systems, HIS 2007

作者： Robb, Katharina Wirjadi, Oliver Schladitz, Katja Image Processing Group Fraunhofer ITWM 67663 Kaiserslautern Germany

ISBN: (纸本)0769529461

Fibrous materials such as fiber-reinforced composites are finding increasing application in the automotive, aerospace, and other industries. Fiber arrangements and defects at microscopic scales have direct impact on their stability. Two-dimensional images obtained by either non-destructive or destructive imaging cannot reveal the full fiber orientation information. Therefore, three-dimensional images obtained by micro computed tomography (μCT) are used. Since segmentation of these image datasets is often difficult due to low contrast, we propose a linear filtering scheme to extract local fiber orientations. Efficient implementations of these filters have been proposed, resulting in practical algorithms with acceptable runtimes in the scale of minutes to at most a few hours for common tomographic image sizes. We show how to condense the local orientation information into visual representations. In contrast to existing 3D orientation estimation methods, our method results in densely sampled orientation maps. The proposed method is applied to images of two different fiber materials and compared to orientation estimates based on measures obtained from integral geometry. We show conformance of the proposed orientation estimation methods with these known methods. © 2007 IEEE.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

An Efficient Technique for Medical image Enhancement Based on Interval Type-2 Fuzzy Set Logic

An Efficient Technique for Medical Image Enhancement Based o...

引用

International conference on Computing, Analytics and Networking (ICCAN)

作者： Bora, Dibya Jyoti Thakur, R. S. Barkatullah Univ Dept Comp Sci & Applicat Bhopal India MANIT Dept Comp Applicat Bhopal India

ISBN: (纸本)9789811078712;9789811078705

Medical images are generally of poor contrast and hence needs a special enhancement technique to improve the visibility before further analysis on those images can be done. The membership function in a Type-1 fuzzy set is not properly defined and hence there lie uncertainties in the result. But, type-2 fuzzy set considers uncertainty in the type-1 membership function itself. Hence, a type-2 fuzzy set based enhancement technique is introduced in this paper. A new membership function is defined. Through the new membership function, the fuzziness of the image is reduced to a great level which automatically enhances its contrast. The results obtained are found better than the traditional state of the art algorithms.

关键词： image enhancement Contrast improvement Entropy Fuzzy image processing Medical image Type-2 fuzzy set

来源：评论

学校读者我要写书评

暂无评论

Hexagonal image Compressionusing Singular Value Decomposition in Python 2

Hexagonal Image Compressionusing Singular Value Decompositio...

引用

2nd International conference on Advances in Computing, Communication, Embedded and Secure systems, ACCESS 2021

作者： Varghese, Prathibha Selva Saroja, G. Arockia Electronics and Communication Department Noorul Islam Centre for Higher Education Tamil Nadu India Dept. Electronics and Communication Engineering Noorul Islam Centre for Higher Education Tamil Nadu India

ISBN: (纸本)9781728171364

With the advent of multimedia technologies in last two decades, there is a widespread need for efficient storage and transmission of data. Dealing with the vast information interchangein this digital era, image compression for reduction in byte size of graphics image file without loss of image quality to an acceptable level becomes the large interest area. Inspired from the biological models of human fovea, hexagonal image processing has gained a lot of attention in artificial intelligence era that deals with the application of image processing system that combines the benefits of biologically motivated structures. In this paper a singular value decomposition (SVD) over hexagonal image compression which is a missing stone in computer vision which provides higher packing density, higher angular symmetry and uniform connectivity. Due to lack of developments in hexagonal imaging devices, different resampling methods like alternate pixel shift method, half pixel shift method, pseudo hexagonal pixel method for sourcing hexagonal images. SVD is one of the powerful cutting-edge technology for image compression algorithms. SVD based image compression is performed on hexagonal grid and is compared with square grid using different parameters like compression ratio, compression size, PSNR and MSE using PYTHON’s SVD function. SVD based hexagonal image achieves the goal of compression by preserving good image quality at higher compression ratios, high computational efficiency, provides low mean square error (MSE), acceptable compression size depending on application and high peak to signal ratio (PSNR). © 2021 IEEE

关键词： Singular value decomposition

来源：评论

学校读者我要写书评

暂无评论

Frame-based modelling and image interpretation of topographic maps

Frame-based modelling and image interpretation of topographi...

引用

Proceedings of the 1995 IEEE International conference on systems, Man and Cybernetics. Part 2 (of 5)

作者： Ebi, Norbert B. Poppenhaeger GRIPS Ltd Neunkirchen Germany

A new method for automatic data acquisition from colored topographic maps is presented. Cartographic paper-based maps describe the real landscape in symbolic and reduced form. The data acquisition from maps provides a spatial reference and a data basis for geographic information systems. Geographic Information systems (GIS) are data processing systems that are used in geographic disciplines, e.g. for environmental planning tasks. In comparison to known algorithms [1], [2], [3], [4], [5], [6] the development of the interpretation strategy has included both the modelling and the evaluation of recursive structures, of conflicts and identities, and the enormous data amount caused by the high information density of topographic maps.

关键词： Geographic information systems

来源：评论

学校读者我要写书评

暂无评论

Tauber theorems for Dirichlet series and fractals

Tauber theorems for Dirichlet series and fractals

引用

13th International conference on Pattern Recognition, ICPR 1996

作者： Chernov, Vladimir M. Image Processing Systems Institute Russian Academy of Sciences 151 Molodogvardejskaya st. Samara 443001 Russia

The connection between fractal properties of sets and meromorphous continuation of some Dirichlet series is considered. Discrete orthogonal bases associated with fractal curves of the special type and fast algorithms ... 详细信息

ISBN: (纸本)081867282X

关键词： Fractals

来源：评论

学校读者我要写书评

暂无评论

A Frequency Domain Processor for Real-Time CDVS Keypoints Extraction 10

A Frequency Domain Processor for Real-Time CDVS Keypoints Ex...

引用

International conference on Signal-image Technology and Internet-Based systems SITIS

作者： Lopez, Giorgio Napoli, Ettore Strollo, Antonio G. M. Univ Naples Federico II Dept Elect & Informat Technol Engn Naples Italy

ISBN: (纸本)9781479979783

Compact Descriptors for Visual Search (CDVS) has been recently proposed as the part of the MPEG-7 standard which encompasses technologies and algorithms for the automatic retrieval of visual information from images and videos. A critical part of these algorithms is the selection of points of interest, also referred to as keypoints, within the given frame. The extracted features need to exhibit robustness against changes as luminance variations, geometrical transformations, and image rescaling. Such characteristics are typical of feature extraction techniques based on the Scale-Space theory and on the Laplacian-of-Gaussian (LoG) kernels. In CDVS, a keypoint detection algorithm based on filtering with LoG kernels is proposed: being these filters non-separable, filtering in space domain requires the computation of 2D-convolutions, which in turn results in the algorithm being heavily demanding in terms of computational cost when performed in such a domain. As a consequence, we propose a frequency domain approach to CDVS keypoint extraction, which is at the core of the processor described in this paper. The main drawback connected to frequency domain operation is related to buffering: to reduce this, the proposed processor operates on a block-by-block basis while exploiting the characteristics of the CDVS algorithm to reduce buffering to a minimum. The architecture proposed herein, deployed on an ALTERA Stratix IV FPGA, is capable of extracting keypoints at a maximum frame rate over 20 fps, proving itself suitable for real-time applications.

关键词： Visual Search MPEG-7 LoG Scale-Space theory real-time video processing FPGA

来源：评论

学校读者我要写书评

暂无评论

An Edge Traffic Flow Detection Scheme Based on Deep Learning in an Intelligent Transportation System

引用

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION systems 2021年第3期22卷 1840-1852页

作者： Chen, Chen Liu, Bin Wan, Shaohua Qiao, Peng Pei, Qingqi Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Zhongnan Univ Econ & Law Sch Informat & Safety Engn Wuhan 430073 Peoples R China

An intelligent transportation system (ITS) plays an important role in public transport management, security and other issues. Traffic flow detection is an important part of the ITS. Based on the real-time acquisition of urban road traffic flow information, an ITS provides intelligent guidance for relieving traffic jams and reducing environmental pollution. The traffic flow detection in an ITS usually adopts the cloud computing mode. The edge of the network will transmit all the captured video to the cloud computing center. However, the increasing traffic monitoring has brought great challenges to the storage, communication and processing of traditional transportation systems based on cloud computing. To address this issue, a traffic flow detection scheme based on deep learning on the edge node is proposed in this article. First, we propose a vehicle detection algorithm based on the YOLOv3 (You Only Look Once) model trained with a great volume of traffic data. We pruned the model to ensure its efficiency on the edge equipment. After that, the DeepSORT (Deep Simple Online and Realtime Tracking) algorithm is optimized by retraining the feature extractor for multiobject vehicle tracking. Then, we propose a real-time vehicle tracking counter for vehicles that combines the vehicle detection and vehicle tracking algorithms to realize the detection of traffic flow. Finally, the vehicle detection network and multiple-object tracking network are migrated and deployed on the edge device Jetson TX2 platform, and we verify the correctness and efficiency of our framework. The test results indicate that our model can efficiently detect the traffic flow with an average processing speed of 37.9 FPS (frames per second) and an average accuracy of 92.0% on the edge device.

关键词： image edge detection Cloud computing Real-time systems Machine learning Object detection Intelligent transportation systems Computational modeling Intelligent transportation system edge computing deep learning traffic flow detection

来源：评论

学校读者我要写书评

暂无评论

Advances in Artificial Intelligence and Its Applications: 14th Mexican International conference on Artificial Intelligence, MICAI 2015

引用

2016年

作者： Obdulia Pichardo Lagunas Oscar Herrera Alcéntara Gustavo Arroyo Figueroa

ISBN: (纸本)9783319271002

The two volume set LNAI 9413 + 9414 constitutes the proceedings of the 14th Mexican International conference on Artificial Intelligence, MICAI 2015, held in Cuernavaca,. Morelos, Mexico, in October *** total of 98 papers presented in these proceedings was carefully reviewed and selected from 297 submissions. They were organized in topical sections named: natural language processing; logic and multi-agent systems; bioinspired algorithms; neural networks; evolutionary algorithms; fuzzy logic; machine learning and data mining; natural language processing applications; educational applications; biomedical applications; image processing and computer vision; search and optimization; forecasting; and intelligent applications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Schedule Your Edit: A Simple yet Effective Diffusion Noise Schedule for image Editing 38

Schedule Your Edit: A Simple yet Effective Diffusion Noise S...

引用

38th conference on Neural Information processing systems, NeurIPS 2024

作者： Lin, Haonan Chen, Yan Wang, Jiahao An, Wenbin Wang, Mengmeng Tian, Feng Liu, Yong Dai, Guang Wang, Jingdong Wang, Qianying School of Comp. Science & Technology MOEKLINNS Lab Xi'an Jiaotong University China College of Comp. Science & Technology Zhejiang University of Technology China School of Auto. Science & Engineering MOEKLINNS Lab Xi'an Jiaotong University China Institute of Cyber-Systems and Control Zhejiang University China SGIT AI Lab State Grid Corporation of China China Baidu Inc. China Lenovo Research China

Text-guided diffusion models have significantly advanced image editing, enabling high-quality and diverse modifications driven by text prompts. However, effective editing requires inverting the source image into a latent space, a process often hindered by prediction errors inherent in DDIM inversion. These errors accumulate during the diffusion process, resulting in inferior content preservation and edit fidelity, especially with conditional inputs. We address these challenges by investigating the primary contributors to error accumulation in DDIM inversion and identify the singularity problem in traditional noise schedules as a key issue. To resolve this, we introduce the Logistic Schedule, a novel noise schedule designed to eliminate singularities, improve inversion stability, and provide a better noise space for image editing. This schedule reduces noise prediction errors, enabling more faithful editing that preserves the original content of the source image. Our approach requires no additional retraining and is compatible with various existing editing methods. Experiments across eight editing tasks demonstrate the Logistic Schedule's superior performance in content preservation and edit fidelity compared to traditional noise schedules, highlighting its adaptability and effectiveness. (Project page: https://***/SYE/). © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The German Traffic Sign Recognition Benchmark: A multi-class classification competition

The German Traffic Sign Recognition Benchmark: A multi-class...

引用

International Joint conference on Neural Networks (IJCNN)

作者： Stallkamp, Johannes Schlipsing, Marc Salmen, Jan Igel, Christian Ruhr Univ Bochum Inst Neuroinformat D-44780 Bochum Germany Univ Copenhagen Dept Comp Sci DK-2100 Copenhagen Denmark

ISBN: (纸本)9781424496365

The "German Traffic Sign Recognition Benchmark" is a multi-category classification competition held at IJCNN 2011. Automatic recognition of traffic signs is required in advanced driver assistance systems and constitutes a challenging real-world computer vision and pattern recognition problem. A comprehensive, lifelike dataset of more than 50,000 traffic sign images has been collected. It reflects the strong variations in visual appearance of signs due to distance, illumination, weather conditions, partial occlusions, and rotations. The images are complemented by several precomputed feature sets to allow for applying machine learning algorithms without background knowledge in image processing. The dataset comprises 43 classes with unbalanced class frequencies. Participants have to classify two test sets of more than 12,500 images each. Here, the results on the first of these sets, which was used in the first evaluation stage of the two-fold challenge, are reported. The methods employed by the participants who achieved the best results are briefly described and compared to human traffic sign recognition performance and baseline results.

关键词： Benchmark testing German Traffic Sign Recognition Benchmark Histograms Humans image color analysis image resolution Lead Training computer vision computer vision driver assistance system driver information systems image classification image processing learning (artificial intelligence) machine learning algorithm multiclass classification competition pattern recognition problem traffic engineering computing

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：