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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems VII"

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Analysis of Optimization on Sparse Matrix Vector Multiplication Model Application in Digital Signal processing 3

Analysis of Optimization on Sparse Matrix Vector Multiplicat...

引用

3rd IEEE International conference on Electrical Power and Energy systems, ICEPES 2024

作者： Shaji, Alden C Khare, Kavita Maulana Azad National Institute of Technology Electronics & Communication Engineering Department Bhopal India

ISBN: (纸本)9798350390728

Conventional digital signal processing (DSP) technology, utilizing DSP and FPGA, excels in real-time signal processing but faces limitations in handling large-scale data and achieving high frequency resolution. This restricts its effectiveness for tasks involving offline data processing, analysis, and mining in applications with extensive data volumes. Some of the SpMV applications in image editing operations like linear filtering, resizing and mixing are reformulated in the SpMV multiplication form. The growing complexity of applications and the demand for top-notch digital data necessitate a boost in processing power. With energy efficiency becoming a critical concern, there is research on designing SpMV algorithms that minimize energy consumption. This is particularly relevant for embedded DSP systems and applications where power efficiency is a key consideration. A comparative study of High-Level Synthesis (HLS) techniques to reduce the power consumption and resource utilization conducted on Xilinx-Zynq 7000 FPGA is presented. This paper explores various HLS pragmas techniques using OpenCL framework applied on Sparse Matrix Vector Multiplication (SpMV) kernel for optimizing power efficiency and resource utilization. HLS has emerged has a pivotal technology for simplifying the design process of complex digital systems by allowing developers to work at higher levels of abstraction, using high-level programming languages. From the analysis, identified the best optimization technique for the low power and the minimum resource utilization for the SpMV implementation on FPGA hence it can be more useful for applications in the field of CNN. © 2024 IEEE.

关键词： High level synthesis

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Research on Parallel Computation and Memory Optimization of Multi-Core Embedded DSP Technology in High Precision Missile Terminal Guidance image Tracking Algorithm 6

Research on Parallel Computation and Memory Optimization of ...

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6th IEEE International conference on Power, Intelligent Computing and systems, ICPICS 2024

作者： Xia, Fuming Jing, Bo Huo, Mingge Jiao, Xiaoxuan Wang, Shenglong Pan, Jinxin School of Aeronautical Engineering Air Force Engineering University Xi'an710038 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China

ISBN: (纸本)9798350374315

This paper mainly discusses how to effectively use multi-core embedded digital signal processor (DSP) technology to realize parallel computation of image tracking algorithm and memory optimization in high precision missile terminal guidance system. With the increasing requirement of missile strike accuracy in modern war, the vision-based terminal guidance technology has been widely concerned because of its strong autonomy and anti-jamming ability. However, such image processing algorithms are usually highly computation-intensive and data dependent, which requires high real-time and hardware resources. In this paper, the key steps of image tracking algorithm are analyzed and reconstructed deeply, and the architecture suitable for parallel processing of multi-core DSP is designed by modularization. The parallel computing advantages of multi-core DSP are given full play through task division and scheduling strategies to improve the execution efficiency and real-time performance of the algorithm. Secondly, the research also focuses on memory optimization, including the design of data cache strategy, reducing data redundancy, improving memory access locality, etc., and strives to maximize the data reading speed and reduce the memory bandwidth pressure under the condition of limited embedded system resources. To sum up, this research is committed to building an efficient and stable multi-core embedded DSP environment, parallel computing model and memory optimization scheme for high-precision missile terminal guidance image tracking algorithm, which has important theoretical value and practical significance for improving the intelligence level and combat efficiency of missile terminal guidance system. © 2024 IEEE.

关键词： Guided missiles

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image processing Implementation to Classify Coffee Fruit Ripeness Using K-Nearest Neighbor (KNN) Algorithm 8

Image Processing Implementation to Classify Coffee Fruit Rip...

引用

8th International conference on Information Management and Technology, ICIMTech 2023

作者： Hussaini Dermawan, M. Farhan Witarsyah, Deden Syamsuar, Dedy Fakhrurroja, Hanif Luthfi, Ahmad Herdiansyah, Muhammad Izman Telkom University Faculty of Industrial Engineering Bandung Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Islamic University of Indonesia Faculty of Industrial Technology Department of Informatics Jogjakarta Indonesia Universitas Bina Darma Informatics Study Program Faculty of Science and Technology Palembang Indonesia

ISBN: (纸本)9798350326093

Coffee is one of the plantation crops that has long been a cultivated plant in Indonesia. The classification of coffee fruit maturity manually still has several weaknesses and requires a long process, has low accuracy and is inconsistent, this is because the determination is made subjectively by coffee farmers. As for the classification of coffee fruit maturity levels automatically, it can be faster with objective determination, therefore the use of image processing is relatively easier, faster, and based on a quantified descriptive assessment to determine coffee maturity. image processing is a method used to process or manipulate images in 2-dimensional form. In the classification process, there are many methods used to obtain classification of objects based on training data. One of the algorithms used for the classification process is K-Nearest Neighbor (KNN). KNN is a classification technique for objects based on training data that is the closest or has similar characteristics to the object. KNN includes supervised learning algorithms, where the results of the new query instance are classified based on the majority of the categories in K-Nearest Neighbors (K-NN). The finding indicated that class classification of ripe and unripe were 88,24 % and 100% respectively with 93,33% accuracy level. © 2023 IEEE.

关键词： Classification (of information)

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image Understanding Through Visual Question Answering: A Review from Past Research 23th

Image Understanding Through Visual Question Answering: A Rev...

引用

23rd International conference on Intelligent systems Design and Applications, ISDA 2023

作者： Yanda, Nagamani Tagore Babu, J. Aswin Kumar, K. Taraka Rama Rao, M. Ranjith Varma, K.V. Rahul Babu, N. GMR Institute of Technology Rajam532127 India

ISBN: (纸本)9783031648465

Visual Question Answering (VQA) lies at the crossroads of computer vision, natural language processing, and deep learning, captivating researchers across various AI domains. This dynamic field involves processing an image alongside a corresponding textual question, generating, or selecting an answer from provided options. The past five years have witnessed substantial advancements in VQA and visual reasoning, fueled by deep learning and extensive annotated datasets. This study presents a comprehensive literature review, delving into the current state-of-the-art from four perspectives: problem definition, existing datasets, literature review, and evaluation metrics. Through a critical analysis, we address dataset limitations and scrutinize contemporary algorithms. Here we use multimodal Fusion, which achieves the state of the art compared to existing methodologies. Moreover, we explore potential future research directions to inspire innovative solutions and applications in this evolving domain, aiming to propel VQA into new realms of exploration and practical utility. This project will allow users to input an image and image-related text so that it will aid the question-answering system. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Deep learning

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A Comparative Analysis Between the Performance of the Extracted Features of JPEG and PNG on a Raspberry Pi Iris Recognition System 38

A Comparative Analysis Between the Performance of the Extrac...

引用

38th IEEE Region 10 conference, TENCON 2023

作者： Martinez, Gio Arturo S. Moralde, Reese Elijah B. Linsangan, Noel B. Ang, Rayellee Myrtle Laire School of Electrical Electronics and Computer Engineering Mapua University Intramuros Manila Philippines

ISBN: (纸本)9798350302196

The image file format used in iris recognition systems has been proven to affect the performance of iris authentication. PNG and JPEG, the image file formats that are among the most common, will be compared in this study by converting a single iris image to the two image file formats, which will then be evaluated using total and average processing time FRR and FAR. The two file formats differ in their used image compression algorithms. JPEG achieves a lossy image compression, which results in irreversible data loss after every compression, using DCT (Discrete Cosine Transform). On the other hand, PNG achieves lossless image compression using the DEFLATE algorithm. Both algorithms' motive is to compress data. The latter, however, executes this without losing data. The image file formats are compared on a Raspberry Pi 4B that runs the iris recognition system utilizing Daugman's algorithm. After conducting 80 trials of iris recognition in the system, the JPEG database resulted in a total and average processing time of 70.8301s and 1.7708s respectively, and a FRR of 0.05 and a FAR of 0.05. Meanwhile, the PNG database yielded a total and average processing time of 72.2576s and 1.8064s respectively, and a FRR of 0.10 and a FAR of 0.05. This comparative study identified that the extracted iris features from JPEG produced better recognition performance results in the implemented iris recognition system over PNG. © 2023 IEEE.

关键词： image compression

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FPGA-Based High-Speed Remote Sensing Satellite image Data Transmission System 10th

FPGA-Based High-Speed Remote Sensing Satellite Image Data Tr...

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10th International conference on Signal and Information processing, Network and Computers, ICSINC 2022

作者： He, Yifeng Sun, Peng Liu, Qian Zhang, Hao Zhao, Dayang Xi’an Institute of Space Radio Technology Xi’an710100 China

ISBN: (纸本)9789811999673

At present, with the increasing number of remote sensing satellite systems established in China, a large amount of remote sensing satellite image data has been obtained. Based on FPGA, this paper studies the transmission of high-speed remote sensing satellite image data, studies the image characteristics, image preprocessing methods and image detection principles of remote sensing satellite images, and analyzes various methods of image preprocessing. For different targets and different image backgrounds, the specific processing algorithms are also different. Only by flexibly using the basic theory of image processing can a good image processing effect be achieved. Among them, the fast connected region labeling algorithm designed and implemented can realize the merging of equivalent pairs while scanning. The results show that the system can reliably implement the algorithm in this paper, complete the processing of image data, and meet the requirements of the project. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Field programmable gate arrays (FPGA)

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Enhancing image Security Using Legacy-Based Encryption With Chaotic Tent Map and Memristor 26

Enhancing Image Security Using Legacy-Based Encryption With ...

引用

26th IEEE Signal processing: algorithms, Architectures, Arrangements, and Applications, SPA 2023

作者： Elnoamy, Omar Gabr, Mohamed Korayem, Youssef Alexan, Wassim El-Aasser, Minar The German University in Cairo Faculty of MET Cairo Egypt The German University in Cairo Faculty of IET Cairo Egypt

ISBN: (纸本)9798350304985

The development and utilization of effective image encryption techniques is seeing an unprecedented need with the advancements in multimedia production and exchange over unsecured networks. In a simultaneous manner, chaotic functions are increasingly being used by scholars to effectuate chaos in a deterministic manner, to develop pseudo-random bit-streams for the construction of encryption keys and substitution boxes. This work proposes the utilization of a 3-stage image encryption scheme. The Tent chaotic map is used in the first stage, followed by a legacy cellular automata S-box in the second stage, and finally a Memristor chaotic system in the third stage. Performance evaluation shows superior entropy performance and comparable values to the literature in terms of other metrics. © 2023 Division of Signal processing and Electronic systems, Poznan University of Technology (DSPES PUT).

关键词： Memristors

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A Certain Investigation on Undersea Water image Object Detection and Classification Using Artificial Intelligence algorithms 3rd

A Certain Investigation on Undersea Water Image Object Detec...

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3rd International conference on Computing and Communication Networks, ICCCN 2023

作者： Sandhya, Kaipa Arumugam, Jayachandran Presidency University Bangalore India

ISBN: (纸本)9789819708918

The increase in the usage of marine resources in recent years has drawn attention toward the underwater image processing research field;however, underwater images face some of the challenges like severe absorption and scattering of water, low contrast, monotonous color, etc., and make a complicated process. In this paper, we made a comprehensive study related to underwater image processing in recent years. The study includes both machine learning and deep learning approaches used for the detection of underwater objects. This study also presents the current scenarios along with future trends and provides better insights into the research direction in underwater image processing. Recently, artificial intelligence (AI) techniques are widely used for the detection and classification process of undersea water object detection and they demonstrated good outcomes. This study categorizes AI into machine learning and deep learning techniques. This study analyzed 31 papers related to underwater image object detection from various publishers like IEEE, Springer, Elsevier, Taylor and Francis, etc. More survey analysis is based on the study of the deep learning model. Hence, this study presents the advantages and the disadvantages of each model with open research challenges of undersea water object detection and classification. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Water absorption

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Synergistic Integration of MRI Prior for Enhanced Photoacoustic Tomography: Advancing Biomedical Imaging Quality 12th

Synergistic Integration of MRI Prior for Enhanced Photoacous...

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12th International conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2024

作者： Krishna Satya Varma, M. Yamini Priyanka, S. Department of IT SRKR Engineering College Chinaamiram Andhra Pradesh Bhimavaram India

ISBN: (纸本)9789819601424

In this research endeavor, we introduce a pioneering strategy to enhance the fidelity of photoacoustic tomography (PAT) images, addressing prevalent artifacts and distortions stemming from acoustic and optical properties of biological tissues. Our approach capitalizes on the synergy between PAT and magnetic resonance imaging (MRI), exploiting MRI's wealth of information on tissue anatomy and composition to refine PAT reconstructions. Through a meticulously designed framework, we integrate advanced image processing methodologies, spanning registration, fusion, and deep learning-based algorithms, to seamlessly merge MRI priors into the PAT reconstruction pipeline. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： image fusion

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Values Definition of the Leading Threshold of the Primary Process Colors by the Method of Color Separation and image Segmentation by Thresholding 6th

Values Definition of the Leading Threshold of the Primary Pr...

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6th conference on Computational Methods in systems and Software (CoMeSySo)

作者： Drofova, Irena Adamek, Milan Tomas Bata Univ Zlin Fac Appl Informat Dept Secur Engn Zlin Czech Republic

ISBN: (纸本)9783031214370;9783031214387

image analysis and image segmentation methods are a current field of computer vision and are applied in many fields. This text deals with image segmentation and defining the leading edge of a color sample. For the experiment, a sample of material printed with process inks and their overprint was used. The printed material is a glossy white paper with primary print process colors Magenta and Yellow. The paper presents the methodology and procedure of image segmentation using the separation of colors into halftone values. From that values, this basic threshold is created and defined. A convulsion mask was used, the maximum target threshold of the given color was obtained from this basic halftone threshold, and its values were defined. Methods of image analysis of color originals offer the potential for use in the field of protection against forgery of works of art, especially in the area of graphic art techniques and their specific areas.

关键词： image analysis image segmentation image processing Processcolor Color separation Threshold

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