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

共 12978 条记录，以下是1181-1190 订阅

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An image processing Application: Design of VLSI based Bilateral Filter using Distance Matrix Method 2

An Image Processing Application: Design of VLSI based Bilate...

引用

2nd IEEE International conference on Advanced Technologies in Intelligent Control, Environment, Computing and Communication Engineering, ICATIECE 2022

作者： Saranya, C. Vijayananth, M.V. Mouleeshwaran, S. Kaviyarasu, D. K.S.Rangasamy College of Technology Department of ECE Tiruchengode India

ISBN: (纸本)9781665493963

The entire design structure is being impacted by advancements in electronic technology, which is posing a number of challenges for digital systems. In the fields of communications, image processing, and multimedia, VLSI-based image filter architectures are essential. Numerous applications based on VLSI architecture experience problems with significant size components that result in a filter design error during the floating-point arithmetic stages. The increased complexity of the filter design's component list is the issue encountered in the VLSI architecture. Noise removal often involves using the image filtering technique. There is a greater need for performance-based hardware sorting algorithms for low power embedded real-Time image filtering applications. Noise often taints an image while being transmitted from one location to another. The purpose of the denoising technique is to reduce noise while keeping any potential signal features that may be significant. Compare to the prior method, the usage of multipliers can be reduced based on the techniques of distance matrix and hardware resource sharing. The speed of the proposed VLSI architecture for the bilateral filter can be faster than the existing approach. © 2022 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Scanning Electron Microscope image Data Acquisition and Transmission System

Scanning Electron Microscope Image Data Acquisition and Tran...

引用

Intelligent Control, Measurement and Signal processing and Intelligent Oil Field (ICMSP), International conference on

作者： Yang Zhang Zuye Wang Yong Zhao School of Instrument Science and Opto-Electronics Engineering Hefei University of Technology Hefei China

ISBN: (数字)9798331516550

ISBN: (纸本)9798331516567

Scanning electron microscopy (SEM) has emerged as a pivotal tool in scientific research and engineering, offering unparalleled insights into the micro- and nano-scale world. However, traditional SEM systems often entail bulky setups and complex data acquisition processes, limiting their accessibility and efficiency in various applications. This paper designs a desktop SEM image data acquisition and transmission system based on FPGA. The system is divided into two parts: signal modulation and AD sampling circuit and image data processing and transmission circuit. By designing a circuit to process SE/BSE signals, signal modulation and analog-to-digital conversion are achieved. The sampling data is processed using the internal resources of the FPGA and transmitted to the PC through the USB3.0 high-speed interface, and finally displayed as a grayscale image. The system realizes real-time collection, processing and transmission of SEM signals, providing convenience and efficiency for scientific research and engineering applications. Experimental verification shows that the system performs well and has certain application potential.

关键词： Scanning electron microscopy Machine learning algorithms Microscopy Data acquisition Modulation Gray-scale Data processing Universal Serial Bus Real-time systems Field programmable gate arrays

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CSIFA: A Configurable SRAM-based In-Memory FFT Accelerator

CSIFA: A Configurable SRAM-based In-Memory FFT Accelerator

引用

International conference on Application Specific systems (ASAP), Architectures and Processors

作者： Yiyang Lin Yi Zou Yanfeng Yang School of Microelectronic South China University of Technology Guangzhou China

ISBN: (数字)9798350349634

ISBN: (纸本)9798350349641

In the era of Artificial Intelligent (AI) and big data, the demand for signal processing algorithms for large datasets has grown across various fields, notably in the application of the Fast Fourier Transform (FFT). This algorithm is crucial in computation and storage-heavy applications like image and radar signal processing, where it has been integral for decades. In-memory computing (IMC), unlike traditional computing models, integrates computation and storage in the same unit, reducing data transfer time and energy costs. This paper presents CSIFA, a hardware accelerator for up to 1024-point FFT algorithm, utilizing SRAM and some other digital logic to enhance efficiency. Our evaluation indicates that CSIFA performing FFT is able to achieve an overall throughput 15MB/s, computational power 6.65mW, and 115.3GOPS, showcasing its high throughput and energy efficiency for edge application scenarios.

关键词： Program processors Fast Fourier transforms Signal processing algorithms systems architecture Random access memory Throughput Energy efficiency

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image to Text Conversion Using Deep Learning algorithms: Survey

Image to Text Conversion Using Deep Learning Algorithms: Sur...

引用

International conference on Advanced Computing and Communication systems (ICACCS)

作者： M. Saranya V. Veera Anusuya R. Vazhan Arul Santhiya R. Srimathi Department of Computer Science and Engineering National Engineering College Kovilpatti India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384376

image Captioning (ICs) seamlessly combines the realms of Computer Vision (CV) and Natural Language processing (NLP) task involved in producing textual sentences that summarise the image content in a way which is understandable to humans. The primary objective is to enable machines to convey the content of images in human-readable language. image understanding and text formation are typically the two primary processes in the image captioning process. A family of Convolutional Neural Network (CNN) is used to retrieve visual information from an input image during the image understanding process. This visual information includes the image's scenes, relationships, and objects. To translate these visual features into coherent and contextually appropriate captions, recurrent neural network, long short-term memory, transformer-based models, etc. are used in the text generation step. In this article, we propose a survey about the previous research paper and the fundamental steps involved in image captioning tasks.

关键词： Surveys Visualization Computer vision Attention mechanisms Computational modeling Semantics Transformers Natural language processing Convolutional neural networks Integrated circuit modeling

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Highly Constrained Coded Aperture Imaging systems Design Via a Knowledge Distillation Approach

Highly Constrained Coded Aperture Imaging Systems Design Via...

引用

IEEE International conference on image processing

作者： Leon Suarez-Rodriguez Roman Jacome Henry Arguello Universidad Industrial de Santander

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

Computational optical imaging (COI) systems have enabled the acquisition of high-dimensional signals through optical coding elements (OCEs). OCEs encode the high-dimensional signal in one or more snapshots, which are subsequently decoded using computational algorithms. Currently, COI systems are optimized through an end-to-end (E2E) approach, where the OCEs are modeled as a layer of a neural network and the remaining layers perform a specific imaging task. However, the performance of COI systems optimized through E2E is limited by the physical constraints imposed by these systems. This paper proposes a knowledge distillation (KD) framework for the design of highly physically constrained COI systems. This approach employs the KD methodology, which consists of a teacher-student relationship, where a high-performance, unconstrained COI system (the teacher), guides the optimization of a physically constrained system (the student) characterized by a limited number of snapshots. We validate the proposed approach, using a binary coded apertures single pixel camera for monochromatic and multispectral image reconstruction. Simulation results demonstrate the superiority of the KD scheme over traditional E2E optimization for the designing of highly physically constrained COI systems.

关键词： Integrated optics image coding Optical design Simulation Neural networks Optical computing Apertures

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Two-step Method Grid Map Merging Based on Corner Points 41

Two-step Method Grid Map Merging Based on Corner Points

引用

第41届中国控制会议

作者： Chong Chai YunZhi Huang Hefei University of Technology School of Electrical and Automation Engineering

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Multi-robot SLAM(Simultaneous Localization and Mapping) can be used in many collaboration-based operations,such as military rescue *** merging is the most obvious solution to the multi-robot ***,traditional corner-based map fusion algorithms failed in complex *** paper proposes a corner-based two-step method for map merging in complex ***,the map is preprocessed,including orthogonal rotation,filtering,and edge *** corners are identified by Harris Corner detection *** constructing a convex quadrilateral based on the corner points, the overlapping area can be selected for the first ***,the intersection of the obtained quadrilateral diagonals is used as a new feature point,and a triangle is constructed for matching to obtain the final overlapping ***,the rotation angle and displacement can be obtained by calculating the transformation *** results show that this method can solve the complex grid map merging problem effectively.

关键词： Multi-robot SLAM Map merging image processing Two-step method

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Real-Time Car Parking Management System

Real-Time Car Parking Management System

引用

Intelligent algorithms for Computational Intelligence systems (IACIS), International conference on

作者： Ramachandra A C H S Jagadeesh Sanjay J C Vinay D H Siddesh H K Department of EEE Nitte Meenakshi Institute of Technology Bengaluru India Department of ECE Atria Institute of Technology Bengaluru India Nitte Meenakshi Institute of Technology Bengaluru India

ISBN: (数字)9798350360660

ISBN: (纸本)9798350360677

Urban areas in countries like India face significant challenges with traffic congestion and parking management, leading to increased fuel consumption, air pollution, and inefficiencies in transportation. We propose Real-Time Car Parking Management System (RTCPMS) to address the issues by developing a smart parking system that leverages image processing with cameras and utilizes microcontrollers for wireless control of peripherals such as gates, indicating LEDs, and LCD displays. The work integrates image processing techniques to monitor parking space occupancy using cameras installed at parking locations. The microcontroller, equipped with Wi-Fi capabilities, is employed to wirelessly control various peripherals within the parking system. Upon approaching a parking location, users receive real-time information on parking availability via LCD displays, while gate access and indication of available spaces are facilitated through LEDs. The implementation of the system accurately detects parking space occupancy, providing users with up-to-date information on available parking spots. By providing real-time information to users and enabling wireless control of parking peripherals, the system contributes to reducing congestion in parking area, minimizing fuel consumption, and promoting environmental sustainability in urban areas. The results obtained during the process are better compared to the existing.

关键词： Wireless communication Microcontrollers image processing Urban areas Aerospace electronics Logic gates Light emitting diodes Real-time systems Liquid crystal displays Fuels

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EM2-YOLO: Lightweight Remote Sensing image Detection 5th

EM2-YOLO: Lightweight Remote Sensing Image Detection

引用

5th International conference on 3D Imaging Technologies—Multidimensional Signal processing and Deep Learning, 3DIT-MSP and DL 2023

作者： Liu, Xinyi Song, Yaolian Wang, Can School of Information Engineering and Automation Kunming University of Science and Technology Yunnan650500 China

ISBN: (纸本)9789819751808

Remote sensing photographs have a wealth of information, and object detection methods are crucial in this. On mobile and embedded platforms, deep learning-based target identification algorithms are challenging to implement. Additionally, the issues of delayed target detection and poor accuracy of small target detection for remote sensing photos must be resolved immediately. To address these issues, we provide EM2-YOLOv4, a simple method for recognizing remote sensing images. MobileNetv2 acts as the backbone network to reduce model complexity, while depth-separable convolution enhances detection speed. Additionally, we introduce a feature enhancement module and an Efficient Channel Attention (ECA) module to improve model accuracy. To address the issue of unequal assignment of positive and negative samples, we incorporate Focal Loss into the loss function. Experimental demonstrate that the model can perform detection at 45 frames per second with an average accuracy of 94.11%. The model has been significantly reduced, as seen by the fact that it is only 48 MB in size, but it still maintains good detection accuracy and accelerates detection. The model is ideal for usage on embedded devices because of this feature. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Optical remote sensing

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Removing Reflective Flare in Real-World Conditions

Removing Reflective Flare in Real-World Conditions

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IEEE International conference on image processing

作者： Fengbo Lan Chang Wen Chen The Hong Kong Polytechnic University

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

The increasing prevalence of mobile devices has led to significant advancements in mobile camera systems and improved image quality. Nonetheless, mobile photography still grapples with flare corruptions such as reflective flare. The absence of a comprehensive real image dataset tailored for mobile phones hinders the development of effective flare mitigation techniques. To address this issue, we present a novel real image dataset specifically designed for mobile camera systems, focusing on flare removal. Capitalizing on the distinct properties of real images, this dataset serves as a solid foundation for developing advanced flare removal algorithms. The dataset comprises over 1,100 pairs of high-quality, full-resolution images for reflective flare, which generate 2,200 paired patches, ensuring broad adaptability across various imaging conditions. Experimental results demonstrate that networks trained with synthesized data struggle to cope with the complex lighting settings present in this real image dataset. Our dataset is expected to enable an array of new research in flare removal and contribute to substantial improvements in mobile image quality, benefiting mobile photographers and end-users alike.

关键词： image quality Photography image recognition Prevention and mitigation Lighting Focusing Cameras

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Optimization of Coupled ARX-Laguerre Multimodel Parameters Using Genetic Algorithm

Optimization of Coupled ARX-Laguerre Multimodel Parameters U...

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International conference on systems and Control (ICSC)

作者： Hajer Benamor Marwa Yousfi Larbi Chrifi Alaoui Tarek Garna Laboratory of Automatic Signal and Image Processing (LARATSI) National Engineering School of Monastir Monastir Tunisia Laboratory of Innovative Technology (LTI UR-UPJV 3899) University of Picardie Jules Verne Amiens France Higher Institute of Applied Science and Technology of Sousse Sousse Tunisia

ISBN: (数字)9798331531812

ISBN: (纸本)9798331531829

This work treats parametric optimization of nonlinear systems using genetic algorithms. The authors focus, in this paper, in combining the ARX-Laguerre model and the multimodel approach with its coupled configuration to develop a model named the coupled ARX-Laguerre multimodel. The proposed model is characterized by its Laguerre poles, Fourier coefficients and weighting functions parameters. The complexity of the model is tightly related to the optimal identification of the Laguerre poles characterizing the model. The authors propose an optimization algorithm of the multimodel parameters (Laguerre poles and weighting functions parameters) based on the genetic to guarantee a significant parametric number reduction with regards to the classic ARX multimodel.

关键词： Uncertainty Solids Genetics Control systems Chemical reactions Iterative algorithms Complexity theory Nonlinear systems Optimization Genetic algorithms

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