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

共 16440 条记录，以下是2051-2060 订阅

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Fast Object Detection Algorithm using Edge-based Operation Skip Scheme with Viola-Jones Method

Fast Object Detection Algorithm using Edge-based Operation S...

引用

IEEE International conference on Artificial Intelligence Circuits and systems (AICAS)

作者： Cheol-Ho Choi Joonhwan Han Jeongwoo Cha Jungho Shin Hyun Woo Oh Pangyo Research and Development (R&D) Center Hanwha Systems Co. Ltd. Seongnam Republic of Korea

ISBN: (数字)9798350383638

ISBN: (纸本)9798350383645

Machine learning approaches are preferred over deep learning in embedded systems due to their resource efficiency. The widely adopted Viola-Jones method and related algorithms are selected for their high detection accuracy and reasonable processing speed. However, a limitation arises as processing time increases with additional classification iterations based on sub-window operations. To address this issue, we propose an enhanced object detection algorithm that incorporates the Viola-Jones method with edge component calibration and an edge-based operation skip scheme. The introduction of edge component calibration ensures detection performance comparable to conventional methods. This scheme, relying on edge values, significantly reduces unnecessary computations in the background, leading to a marked decrease in classification operations compared to conventional methods. Visual comparisons in experimental results demonstrate that our method increases the detection precision factor while maintaining recall. In terms of classification operations, our approach reduces their number by 31.38% to 85.78% compared to conventional methods. In simpler terms, our method improves processing speed by minimizing classification operations, making it well-suited for embedded systems with limited resource utilization.

关键词： Visualization Embedded systems Machine learning algorithms image edge detection Object detection Transforms Classification algorithms

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OFDM Signal processing Based On Tone Reservation and Active Constellation Extension

OFDM Signal Processing Based On Tone Reservation and Active ...

引用

International conference on Signal processing Proceedings (ICSP)

作者： Fengyuan Guo Yujie Zhou xinjian Xu Jianhua Ge School of Communication Engineering Xidian University Xi 'an China

ISBN: (数字)9798350387384

ISBN: (纸本)9798350387391

A significant disadvantage of Orthogonal Frequency Division Multiplexing (OFDM) systems is the high Peak Average Power Ratio (PAPR). Among the various PAPR reduction techniques, probabilistic methods are widely favored due to their non-distortion characteristics. These methods primarily disrupt the phase coherence between subcarriers by incorporating additional data. This paper proposes a combined algorithm named Least Squares Approximation - Tone Reservation - Active Constellation Extension - Bunded Distortion (LSA-TR-ACE-BD) algorithm, which combines the Least Squares Approximation - Tone Reservation (LSA-TR) algorithm with the Least Squares Approximation - Active Constellation Extension - Bunded Distortion (LSA-ACE-BD) algorithm. The simulation results demonstrate that the LSA-TR-ACE-BD algorithm can reduce the PAPR to about 5.6dB with low complexity and low Bit Error Rate (BER), indicating its significant practical application potential in engineering.

关键词： Least squares approximations Simulation Bit error rate Signal processing algorithms Peak to average power ratio Coherence Approximation algorithms Distortion Probabilistic logic Complexity theory

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Optimization of Apriori Algorithm Based on Binary Coding and Matrix processing

Optimization of Apriori Algorithm Based on Binary Coding and...

引用

International conference on Information systems and Computer Aided Education (ICISCAE)

作者： xinxin Han Jiao Wang Xueguan xiong Liuling Wang xi Yang Southwest University of Science and Technology Mianyang China

ISBN: (数字)9798350350760

ISBN: (纸本)9798350350777

This research delves into the classic Apriori algorithm, comprehensively analyzing its concepts, properties, and existing limitations, and provides a detailed demonstration of the algorithm's execution flow through a case study. Aiming at the problems of traditional Apriori algorithms, such as low execution efficiency, heavy I/O, and excessive computation, an enhancement algorithm is proposed: By binary coding, the transaction sets of different items and adopting the storage structure of matrix processing data, Logical AND operations are used to enhance the execution efficiency of the algorithm, it is essential to minimize the number of database scans required during the process of identifying frequent item sets. This practical and efficient optimization algorithm offers hope for improved data mining processes.

关键词： Correlation Memory Encoding Transaction databases Association rule learning Computational efficiency Optimization Information systems

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Application Research of Pointer Instrument Panel Extraction Algorithm Based on Deep Learning

Application Research of Pointer Instrument Panel Extraction ...

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6th International conference on Intelligent Computing and Signal processing (ICSP)

作者： xianwei Zhang Shanlian He School of Computer Science Xi'an Shiyou University Xi'an China

Pointer-type meters can suffer from inefficiencies in using manual data reading due to the lack of digital interfaces. Traditional pointer gauge reading recognition algorithms can only operate in specific environments or fixed locations without high reliability. In this paper, by introducing the traditional dial extraction algorithm Hoff circle detection, we propose the improved Mask R-CNN deep learning algorithm for automatic recognition of pointer-type dashboard based on Mask R-CNN algorithm, and introduce the maximum pooling algorithm for image feature extraction and the improved method of using PrROIPooling pooling technique. Experiments show that the improved Mask R-CNN algorithm improves the target detection accuracy by 2.1% and the instance segmentation accuracy by 1.9%. Compared with the traditional dial localization algorithm, this algorithm has the features of hih accuracy and robustness.

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A Low-Cost Deployment Case Study for Industrial IoT Data Collection and processing

A Low-Cost Deployment Case Study for Industrial IoT Data Col...

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Intelligent Technology and Embedded systems (ICITES), International conference on

作者： Jiajun Zhang Biao Hu College of Engineering China Agricultural University Beijing China

ISBN: (数字)9798331506292

ISBN: (纸本)9798331506308

Despite the widespread implementation of SCADA systems in factories for centralized data management, their functionality is restricted to devices equipped with sensors. Manual readings are still prevalent for critical instruments like temperature and pressure gauges, lacking interfaces, leading to inefficiencies and errors. Upgrading production line sensors with IoT-enabled instruments is costly and disruptive. To tackle this, we propose a cost-effective data acquisition system that leverages edge acquisition devices and deep learning algorithms without altering the existing equipment and processes. Our solution involves installing new sensors or cameras in critical areas and employing image recognition algorithms alongside indirect measurement techniques. This approach enhances the real-time accuracy of data collection, significantly boosts the overall efficiency of the production process, and reduces operating costs.

关键词： Temperature sensors Temperature measurement Deep learning Accuracy image edge detection Data acquisition Data collection Production facilities Sensors Edge computing

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Synergistic Perception of the Binocular Imitating Human Eyes

Synergistic Perception of the Binocular Imitating Human Eyes

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2022 International conference on Mechanical and Electronics Engineering, ICMEE 2022

作者： Ge, Zhaokai xia, xiaohua Qin, Xufang Wang, Gangfeng xiang, Haoming Cao, Yusong School of Construction Machinery Chang'an University Xi'an China

ISBN: (纸本)9781665492201

The binocular system of the human eye can accurately focus on the salient areas in the scene, which has great reference significance for the processing volume of simplified data in vision. In response to this method, we propose a method that mimics the attention mechanism of the human eye to complete the bionic machine vision relative to the human eye. According to the principle of the human eye's attention mechanism, the center of multiple cameras can be overlapped with the center of the saliency area while extracting the visual saliency area through the bionic technology that simulates the biological mechanism. The equipment adopts a symmetrical arrangement in structure to reduce the torsional force required by the motor and make the structure more compact. Functionally, the device integrates multiple modules such as image saliency region extraction, visual servings, and multi-motor collaborative control, and has broad application prospects in robotics and intelligent manufacturing. © 2022 IEEE.

关键词： Binoculars

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Airborne reconfigurable data processing and analysis technology based on air-ground bidirectional link

Airborne reconfigurable data processing and analysis technol...

引用

Big Data & Artificial Intelligence & Software Engineering (ICBASE), International conference on

作者： Hao Wang Youyang Qu Shenghu Liu Guowang Zhang Chinese Flight Test Establishment CFTE Xi’an China

ISBN: (数字)9798331506612

ISBN: (纸本)9798331506629

Airborne real-time data processing is an important way to process flight test data. It plays a very important role in improving the efficiency of data processing, shortening the test flight cycle, and accelerating the delivery of aviation products. This paper studies the airborne reconfigurable data processing and analysis technology based on the air-ground bidirectional link, designs the airborne reconfigurable data processing and analysis architecture, and breaks through key technologies such as multi-data stream real-time processing and analysis technology, dynamic switching technology of analysis algorithms based on state migration, and system configuration management technology for surface air-ground consistency assurance. It realizes functions such as real-time processing of airborne data, real-time analysis of test flight subjects, telemetry downlink of analysis results, and on-demand configuration of two-way links, and promotes the transformation of flight test data processing mode from “pulling the disk, unloading, diversion, processing” to “flying, processing, analyzing, downlinking, and configurable”. This technology effectively improves the ability and efficiency of airborne real-time data processing, and plays a positive role in promoting the transformation and upgrading of data processing mode.

关键词： Wireless communication 5G mobile communication Heuristic algorithms Configuration management Switches Data processing Real-time systems Air to ground communication Telemetry Surface treatment

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Artificial Intelligence in Natural Disaster: Data Crawling- and Text Mining-Based Literature Review 8

Artificial Intelligence in Natural Disaster: Data Crawling- ...

引用

8th International conference on Informatics and Computing, ICIC 2023

作者： Ramadhan, Zhafran Yunita, Ariana Universitas Pertamina Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350342604

A literature review is an essential part of research. Beginning researchers who would like to conduct research in any field commonly review previous papers to identify trends and gaps in research. However, conducting a literature review is challenging, particularly for novice researchers. First, synthesising previous related works can be time-consuming. Second, accessing expensive databases such as Scopus and Web of Science might be inaccessible for novice researchers in developing countries. Thus, the purpose of this paper is to present a review performed by data crawling Arxiv and using latent Dirichlet allocation (LDA), a topic modelling algorithm. In this paper, we provide an overview of the topic models of natural disasters and artificial intelligence. Papers from 2017-2022 were crawled using Python with specific keywords, and only papers written in English were eligible for further analysis. Then, the papers were pre-processed by lowering the text, removing punctuation and stop words, tokenising, and lemmatising with POS tagging techniques. Pre-processed papers were then trained using the LDA algorithm. For evaluation, coherence metrics were used to determine the optimal number of topics. There were five topics resulting from the topic modelling algorithm. The clusters were qualitatively analysed and labelled as image classification, algorithms, social media analysis, natural language processing, and machine learning. Further findings are also discussed. © 2023 IEEE.

关键词： Natural language processing systems

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

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

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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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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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