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

共 12950 条记录，以下是1201-1210 订阅

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Raindrop Removal for In-Vehicle Camera images with Generative Adversarial Network

Raindrop Removal for In-Vehicle Camera Images with Generativ...

引用

2022 IEEE International conference on systems, Man, and Cybernetics, SMC 2022

作者： Zhao, Zihao Jiang, Min Guo, Jia Yang, Xiaoyu Hu, Yudie Zhou, Xianlong Wuhan University of Science and Technology College of Computer Science and Technology Wuhan430065 China Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan430065 China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Raindrop removal for in-vehicle camera images is useful for surveillance and analysis system such as intelligent driving or case diagnosis. As in rainy days, images taken by in-vehicle cameras such as monitor or drive recorder often suffer from noticeable image degradation, and make it difficult to identify the objects on the road. With the uncertainty of raindrop distribution and the complexity of raindrop status, the attached raindrops of in-vehicle camera images can have different effects. And the large-diameter raindrop will greatly reduce the image quality. However, most of the popular deraining algorithms have been successful in recovering images with small raindrop noise and tiny image distortion, but fails to restore those with raindrops covering large areas. We propose a single image raindrop removal network based on Generative Adversarial Network for in-vehicle camera images. We incorporate two overlapping attention layers into the deraining network, which adopt task-driven visual attention and content perception mechanism. The former obtains features by recursive neural network to guide network more interested in the raindrop regions and the surrounding structures, while the content perception schema extracts the features far from raindrops. Moreover, we collect a new benchmark for In-Vehicle Camera image Deraining (IVCRID), it chooses in-vehicle camera images from various deraining dataset. The experimental results show that the proposed deraining network outperforms other state-of-the-art raindrop removal methods in image recovering test on the IVCRID dataset and also has the best performance on the experiments of traffic objects detection. © 2022 IEEE.

关键词： Generative adversarial networks

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A GPU Parallel Stitching Algorithm for Low-Altitude Parallax Scenes

A GPU Parallel Stitching Algorithm for Low-Altitude Parallax...

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Machine Learning and Computer Application (ICMLCA), International conference on

作者： Sha Liu Shan Zhou Yan Hu China Electronics Technology Group Corp 54th Research Institute Shijiazhuang China China Electronics Technology Group Corp 20th Research Institute Xi'an China School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (数字)9798331530334

ISBN: (纸本)9798331530341

Panorama stitching of low-altitude captured images is a very interesting and challenging task. Since 3D scenes are not planar, there may be significant changes in the relative positions of scene structures in each perspective in the images, thus causing parallax. Existing image stitching algorithms often fail in parallax scenes and are not efficient enough to meet the real-time processing requirements of drones. To address this problem, we introduce gridded dense projection estimation and design a parallel computing unit suitable for GPUs for rapid modeling of projection fields. Experimental results show that our algorithm significantly outperforms the comparison algorithms in terms of computational performance, has high real-time performance, and achieves nearly the same level of stitching quality and naturalness.

关键词： Three-dimensional displays Computational modeling Graphics processing units Machine learning Parallel processing Real-time systems Partitioning algorithms Computational efficiency image stitching Periodic structures

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

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

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

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

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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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Autonomous Drone for Surveying Flooded Area and Performing Optimal Rescue Operation Using image processing

Autonomous Drone for Surveying Flooded Area and Performing O...

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conference on Modeling of systems Circuits and Devices (MOS-AK India)

作者： L David William Raj S Sampreeth R Sri Lakshmi Leena Juliet S Sneha Department of ECE MVJ College of Engineering Bangalore India

ISBN: (数字)9798350395556

ISBN: (纸本)9798350395563

During life threatening conditions caused due to natural disasters, search and rescue operations manually has not been possible to implement quickly. To overcome this issue, the proposed methodology provides a solution of using an autonomous drone with the help of image processing techniques in flooded scenarios. When any victims are identified, our proposed system aids in the rescue operations by visually screening the flooded areas and sending a signal to the rescue team. Using this UAV camera several image processing algorithms are performed to detect survivors to approximate the area of the flooded region.

关键词： Technological innovation image segmentation Disasters Autonomous aerial vehicles Cameras Approximation algorithms Classification algorithms

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Scanning Electron Microscope image Data Acquisition and Transmission System

Scanning Electron Microscope Image Data Acquisition and Tran...

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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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Real-Time Car Parking Management System

Real-Time Car Parking Management System

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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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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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image to Text Conversion Using Deep Learning algorithms: Survey

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

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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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