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检索条件"任意字段=4th International Conference on Parallel and Distributed Methods for Image Processing IV"

共 46 条记录，以下是1-10 订阅

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Efficient Allocation of image Recognition and LLM Tasks on Multi-GPU System 15th

Efficient Allocation of Image Recognition and LLM Tasks on...

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15th international conference on parallel processing and Applied Mathematics, PPAM 2024

作者： Lawenda, Marcin Samborski, Krzesimir Khloponin, Kyrylo Szustak, Lukasz Poznan Supercomputing and Networking Center Jana Pawla II 10 Poznań61-139 Poland Czestochowa University of Technology Dąbrowskiego 69 Częstochowa42-201 Poland

ISBN: (纸本)9783031857027

this work is concerned with the evaluation of the performance of parallelization of learning and tuning processes for image classification and large language models. For machine learning model in image recognition, various parallelization methods are developed based on different hardware and software scenarios: simple data parallelism, distributed data parallelism, and distributed processing. A detailed description of presented strategies is given, highlighting the challenges and benefits of their application. Furthermore, the impact of different dataset types on the tuning process of large language models is investigated. Experiments show to what extent the task type affects the iteration time in a multi-GPU environment, offering valuable insights into the optimal data utilization strategies to improve model performance. Furthermore, this study leverages the built-in parallelization mechanisms of PyTorch that can facilitate these tasks. Furthermore, performance profiling is incorporated into the study to thoroughly evaluate the impact of memory and communication operations during the training/tuning procedure. Test scenarios are developed and tested with numerous benchmarks on the NVIDIA H100 architecture showing efficiency through selected metrics. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Contrastive Learning

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A Review on parallel Medical image processing on GPU 4

A Review on Parallel Medical Image Processing on GPU

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4th international conference on Software Engineering and Computer Systems (ICSECS)

作者： Khor, Hui Liang Liew, Siau-Chuin Zain, Jasni Mohd. Univ Malaysia Pahang Fac Comp Syst & Software Engn Lebuhraya Tun Razak Kuantan 26300 Pahang Darul Ma Malaysia

ISBN: (纸本)9781467367226

An efficient implementation are necessary, as most medical imaging methods are computational expensive, and the amount of medical imaging data is growing. Graphic processing units (GPUs) can solve large data parallel problems at a higher speed than the traditional CPU, while being more affordable and energy efficient than distributed systems. this review investigates the use of GPUs to accelerate medical imaging methods. A set of criteria for efficient use of GPUs are defined. the review concludes that most medical image processing methods may benefit from GPU processing due to the methods' data parallel structure and high thread count. However, factors such as synchronization, branch divergence and memory usage can limit the speedup.

关键词： parallel computing Medical image processing GPU multicores

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Tracking the attitude of an aircraft with a single imaging sensor using numerical optimization-based methods

Tracking the attitude of an aircraft with a single imaging s...

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4th international conference on parallel and distributed methods for image processing iv

作者： Park, Y Shin, S Chun, J Agcy Def Dev Taejon 305600 South Korea

ISBN: (纸本)0819437638

We shall show how to extract various important information on the motion of a target (enemy aircraft) from a sequence of its image frames obtained using a single imaging sensor which is mounted on an aircraft. Specifically, we present an algorithm which estimates following 12 parameters of an enemy aircraft from its image sequence;position (three), linear velocity (three), attitude (three), instantaneous angular velocity (three) and optional acceleration (three). To extract the attitude, we use a matching algorithm for the captured image frame to the modeled image. the objective function is the value of correlation between these two images, and we use simulated annealing and downhill simplex methods for maximizing the objective function. Finally, estimation of the position and the attitude is accomplished with a 12-state extended Kalman filter. through simulations, we show that the proposed algorithm is superior to conventional algorithms which do not use the attitude information.

关键词： Target Tracking simulated annealing Euler angles Kalman filter

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Intelligent agent support for automated radiology exam

Intelligent agent support for automated radiology exam

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4th international conference on parallel and distributed methods for image processing iv

作者： Shang, Y Popescu, M Univ Missouri Dept Comp Sci & Comp Engn Columbia MO 65211 USA

ISBN: (纸本)0819437638

A difficult problem in automatic medical image understanding is that for every image type such as x-ray and every body organ such as heart, there exist specific solutions that do not allow for generalization. Just collecting all the specific solutions will not achieve the vision of a computerized physician. To address this problem, we propose an intelligent agent approach that is based on agent-oriented programming and the concept of active fusion. the advantage of agent-oriented programming is that it combines the benefits of object-oriented programming and expert system. For radiology image understanding, we present a multi-agent system that is composed of two major types of intelligent agents: radiologist agents and patient agents. A patient agent asks for multiple opinions from radiologist agents in interpreting a given set of images and then integrates the opinions. A radiologist agent decomposes the image recognition task into smaller problems that are solved collectively by multiple intelligent sub-agents. Finally, we present a preliminary implementation and running examples of the multi-agent system.

关键词： intelligent agent radiology image interpretation information fusion

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FPGA-based parallel implementation for the lifting discrete wavelet transform

FPGA-based parallel implementation for the lifting discrete ...

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4th international conference on parallel and distributed methods for image processing iv

作者： Aranki, N Jiang, WQ Ortega, A CALTECH Jet Prop Lab Pasadena CA 91101 USA

ISBN: (纸本)0819437638

the rapidly increasing popularity of the discrete wavelet transform (DWT) as an effective tool in many signal processing and data compression applications, and its integration into JPEG 2000 has given rise to various DWT algorithms and their VLSI implementations to reduce complexity and enhance performance, In this paper, we present an efficient hardware implementation of the discrete wavelet transform and its deployment on a reconfigurable FPGA based platform. Our implementation is a novel architecture based on the lifting factorization of the wavelet filter banks. this factorization leads to a block based parallel DWT architecture suitable for hard-ware implementation. To overcome the communication overhead associated with the DWT block transform, we utilize the new Overlap-State(1,2) technique to compute the DWT near block boundaries. A VHDL description of the lifting polyphase factorization architecture was developed and ported to an FPGA hardware platform that was chosen to allow partial and full reconfigurability to accommodate Various applications with different filter banks. Our hardware implementation improves the performance by better than twofold speed up when compared to an efficient pipelined FPGA based implementation.

关键词： discrete wavelet transform field programmable gate array(FPGA) parallel architecture overlap-state split and merge hardware implementation reconfigurable platform

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Research on parallel Detection Technology of Remote Sensing Object Based on Deep Learning 4

Research on Parallel Detection Technology of Remote Sensing ...

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4th international conference on Intelligent Autonomous Systems (ICoIAS)

作者： Zhang, Chengguang Zhang, Xuebo Jiang, Min Space Engn Univ Sch Grad Beijing Peoples R China Space Engn Univ Sch Space Informat Beijing Peoples R China

ISBN: (纸本)9781665441957

In recent years, methods based on deep learning have become a hot spot and trend in the field of remote sensing object detection, and a series of encouraging results have been achieved. With the development of science and technology, people's technology and ability to acquire remote sensing data have been comprehensively improved, and high-resolution large-scale remote sensing image data has increased dramatically. However, the current mainstream object detection models cannot directly input large-scale high-resolution images for prediction. this paper proposes a remote sensing object parallel detection algorithm, which uses the mpi4py module to realize multi-CPU+GPU distributed parallel processing. Based on the yolov4 object detection model, it can detect remote sensing images of any scale without reducing the prediction accuracy. And shorten the object detection time according to the number of distributed nodes. the experimental results show that the parallel algorithm has a high speedup ratio, and the parallel detection technology has a good development prospect in the field of remote sensing image object detection.

关键词： remote sensing object detention deep learning parallel processing

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Virtual video tape: A novel development tool for real-time motion image understanding

Virtual video tape: A novel development tool for real-time m...

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4th international conference on parallel and distributed methods for image processing iv

作者： Mizoguchi, H Hidai, K Hiraoka, K Shigehara, T Mishima, T Saitama Univ DICS Urawa Saitama 3388570 Japan

ISBN: (纸本)0819437638

this paper proposes Virtual Video Tape (WT). It is a randomly accessible motion image recorder in main memory. VVT is realized with only software, not hardware. It is intended as a tool for real-time motion image understanding research. Recent remarkable progress of PC hardware enables to use gigabyte order main memory. By utilizing such large sized memory, there is a possibility to realize motion image recorder with software. thus we propose VVT as an example of this kind image recorder. Utilizing current components, recording time fan be expected as minutes order. Since the proposed VVT is fully digital, there is no analog medium nor possibility for degradation of image quality. Since there is no deterioration of playback image and no rewinding. VVT must contribute to program development for motion image understanding. Based upon the proposed idea, the authors have implemented a prototype VVT and used the prototype to develop visual tracking, real-time face detection, and so forth. through the implementation and experience of the usage, we have confirmed feasibility and effectiveness of the proposed idea. In this paper, the authors discuss background, required functions and structure of the recorder. Some implementation issues are also described.

关键词： solid state video recorder deterioration-free rewinding-free randomly accessible

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Task Distribution Method for Index Classification based on Color Segmentation in Remote Sensing 4

Task Distribution Method for Index Classification based on C...

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4th international conference on Advanced Information Technologies, ICAIT 2020

作者： Htun, Yan Naing Aye, Bawin Aung, Aung Higher Education Center Department of Computer Technology Pyin Oo Lwin Myanmar

ISBN: (纸本)9781728183640

Digital processing of remotely sensed image data has been great importance in recent times. this research work discusses task distribution method in parallel image processing and load balancing under the circumstance of multi-Tasks and multi-processors in remote sensing. Task distribution method can speed up computation and improve efficiency and perform larger computations which are not possible on single processor system. the tasks are distributed based on the segmentation of color and the Support Vector Machine (SVM) is used to classify the indices of the input image and intends to design and improve the color segmentation based task distribution method for index classification using machine learning. In the system, the RGB satellite image is used as an input image and the output is the four indices of forest, building, road and land the results of the system are more accurate and less time consumption than non-distributed computing methods. It is implemented in MATLAB platform with parallel computation toolbox because the system can solve computationally and data-intensive tasks using multicore processors and clusters of computer. © 2020 IEEE.

关键词： image enhancement

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4th international ACPC conference on parallel Computation, ACPC 1999

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4th international ACPC conference on parallel Computation, ACPC 1999

ISBN: (纸本)3540656413

the proceedings contain 69 papers. the special focus in this conference is on parallel Numerics, parallel Computing in image processing, Video processing, and Multimedia. the topics include: Non-standard parallel solution strategies for distributed sparse linear systems;optimal tridiagonal solvers on mesh interconnection networks;parallel pivots LU algorithm on the cray T3E;experiments with parallel one-sided and two-sided algorithms for SVD;combined systolic array for matrix portrait computation;a class of explicit two-step runge-kutta methods with enlarged stability regions for parallel computers;a parallel strongly implicit algorithm for solution of diffusion equations;a parallel algorithm for lagrange interpolation on k-ary n-cubes;long range correlations among multiple processors;a monte-carlo method with inherent parallelism for numerical solving partial differential equations with boundary conditions;blocking techniques in numerical software;HPF and numerical libraries;an object library for parallel sparse array computation;performance analysis and derived parallelization strategy for a SCF program at the hartree fock level;computational issues in optimizing ophthalmic lens;parallel finite element modeling of solidification processes;architectural approaches for multimedia processing;on parallel reconfigurable architectures for image processing;parallel multiresolution image segmentation with watershed transformation and solving irregular inter-processor data dependency in image understanding tasks.

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A Novel Hybrid Approach for image Fusion using DCT and SML 4

A Novel Hybrid Approach for Image Fusion using DCT and SML

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4th IEEE international conference on parallel, distributed and Grid Computing (IEEE PDGC)

作者： Sonam Kumar, Manoj BBA Univ Dept Comp Sci Lucknow Uttar Pradesh India

ISBN: (纸本)9781509036691

image fusion synthesizes two or more source images having same view into a single fused image, which contains all significant details of the scene. this chapter proposes a new image fusion approach based on discrete cosine transform (DCT) and sum-modified-laplacian (SINIL) in stationary wavelet transform (SWT) domain. Here, two source images of less information are fused to produce a more informative and better visual quality image. the performance of the proposed method is evaluated on various categories of multi-focus images and compared with some existing fusion methods. the simulation results exhibit the better performance of the proposed methods in both quantitative and qualitative measurements.

关键词： image fusion multifocus image fusion stationary wavelet transform discrete cosine transform sum-modified-laplacian

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