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检索条件"任意字段=12th International Conference on Computing and Pattern Recognition, ICCPR 2023"

共 284 条记录，以下是11-20 订阅

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HIGH PERFORMANCE computing FOR LAND COVER DYNAMICS 12

HIGH PERFORMANCE COMPUTING FOR LAND COVER DYNAMICS

引用

conference C on Signal Processing and conference D on Parallel computing, at the 12th IAPR international conference on pattern recognition

作者： PARULEKAR, R SALTZ, J DAVIS, L SUSSMAN, A CHELLAPPA, R TOWNSHEND, J UNIV MARYLAND INST ADV COMP STUDIESCOLLEGE PKMD 20742

ISBN: (纸本)0818662751

We present the overall goals of our research program on the application of high performance computing to remote sensing applications, specifically applications in land cover dynamics. this involves developing scalable and portable programs for a variety of image and map data processing applications, eventually integrated with new models for parallel I/O of large scale images and maps. After an overview of the multiblock PARTI run time support system, we explain extensions made to that system to support image processing applications, and then present an example involving multiresolution image processing. Results of running the parallel code on both a TMC CM5 and an Intel Paragon are discussed. © 1994 IEEE.

关键词： Remote sensing

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RADIAL HOMOMORPHIC DECONVOLUTION OF B-MODE MEDICAL ULTRASOUND IMAGES 12

RADIAL HOMOMORPHIC DECONVOLUTION OF B-MODE MEDICAL ULTRASOUN...

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conference C on Signal Processing and conference D on Parallel computing, at the 12th IAPR international conference on pattern recognition

作者： TAXT, T UNIV BERGEN MED IMAGE & PATTERN ANAL SECTN-5009 BERGENNORWAY

ISBN: (纸本)0818662751

Describes how homomorphic deconvolution can be used to improve the radial resolution of in vitro and in vivo medical ultrasound images. Each of the recorded radiofrequency ultrasound beams used to form the image was considered as a finite depth sequence of length N, and was weighted with the same exponential depth sequence to create at least some minimum phase sequences. the mean value at each depth sample of the complex cepstrum sequences was computed, and the low depth portion of this mean sequence was taken as the complex cepstrum representation of the ultrasound pulse. It was transformed back to the Fourier frequency domain, and was used to compute the deconvolved echo depth sequence. the method gave substantial improvement in the radial resolution of B-scan images of a tissue mimicking phantom and of human tissues in vivo without significant amplification of the image noise.

关键词： Deconvolution Ultrasonic imaging Biomedical imaging Image resolution In vivo Cepstrum In vitro Radio frequency Pulse amplifiers Back

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DUAL GRAPH CONTRACTION FOR IRREGULAR PYRAMIDS 12

DUAL GRAPH CONTRACTION FOR IRREGULAR PYRAMIDS

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conference C on Signal Processing and conference D on Parallel computing, at the 12th IAPR international conference on pattern recognition

作者： WILLERSINN, D KROPATSCH, WG VIENNA TECH UNIV INST AUTOMAT 1832DEPT PATTERN RECOGNIT & IMAGE PROCA-1040 VIENNAAUSTRIA

ISBN: (纸本)0818662751

A new algorithm for building irregular pyramids is presented. the algorithm is based on only two basic operations on graphs, contraction and removal of edges. By making use of the concept of dual graphs, the algorithm overcomes the problem of unbounded vertex degree proper to the existing approach to building irregular pyramids. this boundedness extends the scope of parallel, degree preserving graph contraction also to irregular structures. Our method can be applied to all problems in which a 2D discrete space can be represented by a planar graph. Four-connected square grids, region adjacency graphs, Voronoi diagrams and Delaunay triangulations are examples of such plane representions. © 1994 IEEE.

关键词： Graphic methods

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WHY LINEAR ARRAYS ARE BETTER IMAGE PROCESSORS 12

WHY LINEAR ARRAYS ARE BETTER IMAGE PROCESSORS

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conference C on Signal Processing and conference D on Parallel computing, at the 12th IAPR international conference on pattern recognition

作者： JONKER, PP DELFT UNIV TECHNOL FAC APPL PHYSPATTERN RECOGNIT SECT2600 GA DELFTNETHERLANDS

ISBN: (纸本)0818662751

the four main characteristic architectures for low-level image processing are the Square Processor Array (SPA) or mesh, the Linear Processor Array (LPA) or scanning array, the Pipeline (PL) and the Pyramid (PYR). In this paper a theoretical study is presented which leads from a taxonomy of low-level image processing operations and a theoretical model of a nearest neighbour connected processor to the combinations of 7 possibilities to exchange parallel for sequential solutions when designing an architecture. the implementation of two "standard"image processing routines on the theoretical processor, skeletonization of a binary image and shading correction in a greyvalue image, while making the design decisions in line with the solutions commonly found in the four characteristic architectures, showed that Linear Processor Arrays when properly designed, seem to offer the best speed / efficiency combination even for processing images at video speed. © 1994 IEEE.

关键词： Architecture

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Semantic Filtering Global and Local Embeddings Fusion for Few-Shot Image Classification 12

Semantic Filtering Global and Local Embeddings Fusion for Fe...

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12th international conference on computing and pattern recognition, iccpr 2023

作者： Nong, Luyu Wu, Min Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China

ISBN: (纸本)9798400707988

Neural networks have demonstrated superior performance in image classification tasks, however, acquiring sufficient labeled data for training them in real-world scenarios remains challenging. Few-shot learning (FSL) was proposed to address this challenge in low-data scenarios and has attracted considerable attention in recent years. In few-shot image classification tasks, most of the existing FSL methods focus on designing discriminative network structures for exploring image features, either neglecting semantic information that is crucial for accurate classification, or tending to prioritize either global or local image features. To address this issue, we propose in this work a novel model Semantic Filtering Global and Local embeddings for fusion (SFGL) for few-shot image classification. SFGL effectively integrates both global and local features while leveraging semantic information. Extensive experiments conducted on benchmark datasets demonstrate that our proposed SFGL model outperforms state-of-the-art methods in FSL tasks. © 2023 ACM.

关键词： Image classification

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VLSI ARRAYS FOR SPEECH PROCESSING WIth LINEAR PREDICTIVE CODING 12

VLSI ARRAYS FOR SPEECH PROCESSING WITH LINEAR PREDICTIVE COD...

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conference C on Signal Processing and conference D on Parallel computing, at the 12th IAPR international conference on pattern recognition

作者： TANG, YY LI, T SUEN, CY CONCORDIA UNIV CTR PATTERN RECOGNIT & MACHINE INTELLIGENCEMONTREALPQ H3G 1M8CANADA

ISBN: (纸本)0818662751

the covariance analysis of linear predictive coding has wide applications, especially in speech recognition and speech signal processing. Real-time applications demand very high processing speed for linear predictive coding analysis. VLSI technology which possesses properties of low-cost, high-speed and massive computing capabilities is a suitable candidate. In this paper, systolic array processors for the covariance analysis of linear predictive coding are developed. the covariance analysis of linear predictive coding contains a large set of irregular and nested recurrence equations. Systolizing the algorithm is a difficulty task for such a complex problem. Existing methods of systematic design for systolic arrays are not much helpful to this problem. To overcome it, a break-combination method is presented in this paper. In this manner, the task is first decomposed and then mapped onto several interconnected systolic arrays. the resulting systolic arrays of the sub problems are then combined to form a complete solution. © 1994 IEEE.

关键词： Systolic arrays

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SURVEY OF PARALLEL ALGORIthMS FOR STRUCTURAL pattern MATCHING 12

SURVEY OF PARALLEL ALGORITHMS FOR STRUCTURAL PATTERN MATCHIN...

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conference C on Signal Processing and conference D on Parallel computing, at the 12th IAPR international conference on pattern recognition

作者： GUERRA, C UNIV PADUA DIPARTIMENTO ELETTR & INFORMATI-35100 PADUAITALY

ISBN: (纸本)0818662751

Matching is an important pari of a model-based object recognition system. Matching is a difficult task, for a number of reasons. First, in a number of recognition systems matching is formulated as a combinatorial problem with exponential worst-case complexity. thus, heuristics are needed to reduce the complexity by pruning the search space. Second, images do not present perfect data: noise and occlusion greatly complicate the task. Finally, even at moderate image resolutions the amount of data to be handled is such that this task cannot be done in real-time on supercomputers. Although no existing visual system can solve the general recognition problem, some existing approaches have obtained acceptable results for limited domains or simple scenes. Surveys of many sequential approaches to matching in recognition systems can be found in [2], [7], [18]. Comparatively, much less work has been done on parallel matching, despite the great need for speeding up the process. Parallel algorithms have oflen to be designed from scratch, and the recognition problem itself oflen requires reformulation since many of the proposed sequential algorithms do not lend themselves naturally to efficient parallel implementations. In this paper, we survey some of the existing parallel matching algorithms for 2D and 3D objects. Some of these algorithms have been implemented on SIMD architectures such as the Connection Machine or MasPar, or MIMD machines such as the Intel Touchstone Delta;other algorithms have been developed for the PRAM model of computation. © 1994 IEEE.

关键词： Parallel algorithms

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Complexity vs. Performance in Granular Embedding Spaces for Graph Classification 12th

Complexity vs. Performance in Granular Embedding Spaces for ...

引用

12th international Joint conference on Computational Intelligence (IJCCI) / 12th international conference on Evolutionary Computation theory and Applications (ECTA)

作者： Baldini, Luca Martino, Alessio Rizzi, Antonello Univ Roma La Sapienza Dept Informat Engn Elect & Telecommun Via Eudossiana 18 I-00184 Rome Italy

ISBN: (纸本)9789897584756

the most distinctive trait in structural pattern recognition in graph domain is the ability to deal with the organization and relations between the constituent entities of the pattern. Even if this can be convenient and/or necessary in many contexts, most of the state-of the art classification techniques can not be deployed directly in the graph domain without first embedding graph patterns towards a metric space. Granular computing is a powerful information processing paradigm that can be employed in order to drive the synthesis of automatic embedding spaces from structured domains. In this paper we investigate several classification techniques starting from Granular computing-based embedding procedures and provide a thorough overview in terms of model complexity, embedding space complexity and performances on several open-access datasets for graph classification. We witness that certain classification techniques perform poorly both from the point of view of complexity and learning performances as the case of non-linear SVM, suggesting that high dimensionality of the synthesized embedding space can negatively affect the effectiveness of these approaches. On the other hand, linear support vector machines, neuro-fuzzy networks and nearest neighbour classifiers have comparable performances in terms of accuracy, with second being the most competitive in terms of structural complexity and the latter being the most competitive in terms of embedding space dimensionality.

关键词： Structural pattern recognition Supervised Learning Embedding Spaces Granular computing Graph Edit Distances

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Intensified Biological Signature recognition in the Wild: A Case Study 12

Intensified Biological Signature Recognition in the Wild: A ...

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12th international conference on computing Communication and Networking Technologies, ICCCNT 2021

作者： Gandhi, Vidhyotma Singh, Jaiteg Chitkara Institute of Engineering and Technology Chitkata University Punjab India

ISBN: (纸本)9781728185958

the biological signature recognition seems to be a solved problem, but when these systems are tested in the wild their accuracy collapsed abruptly. A case study of "Face recognition through Camera (FRTC)" was designed to make a state of art for biological signature recognition in the wild system with minimum data set required to provide the highest accuracy. the FRTC system was designed by integrating the best qualities of modern recognition systems present in recent times (OpenCV and Face API) to intensify the biological signature recognition in the wild. the case study FRTC would be tested with the classroom attendance without prior information to the students. It was expected that FRTC would be more accurate than OpenCV and Face API. the results have shown the FRTC is more accurate, 7.02% and ~1% than OpenCV and Face API respectively. © 2021 IEEE.

关键词： pattern matching

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Analysis and implementation of vehicle license plates detection and recognition tool 12

Analysis and implementation of vehicle license plates detect...

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12th international conference on Software Process Improvement (CIMPS)

作者： Valdiviezo Saul, Maldonado Santacruz Eduardo, Vazquez Univ Autonoma Metropolitana Dept Matemat Mexico City Mexico

ISBN: (纸本)9798350358568

Vehicle license plate detection and recognition it's a multi stage process, image pre- processing, license plate location, character location and recognition. We analyzed the multiple methodology used during this process, their features and results and implemented an algorithm that executes it. We applied a hybrid algorithm for plate location, a mathematical one for segmentation and a convolutional neural network for recognition, obtaining 98% in segmentation and recognition.

关键词： Digital image License plate detection Machine learning Software engineering pattern recognition

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