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

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UAV image Denoising based on Swin Deformer for Power System Condition Monitoring

UAV Image Denoising based on Swin Deformer for Power System ...

引用

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

作者： Dong Wang Linwei Ye Department of Mechanics and Robotics Systems Xi’an Jiaotong-Liverpool University Suzhou China Department of Information Management and Information System Xi’an Jiaotong-Liverpool University Suzhou China

In order to improve the quality of UAV transmission line inspection pictures and ensure the effectiveness of the defect recognition network, this paper proposes a model based on Swin Deformer to denoise the pictures. The data set of this method is the original data set collected by UAV, and the test set and training set are obtained by classifying the raw data. At the same time, Gaussian noise is added to generate tags to ensure the effect of supervised learning. Finally, the test set is input into the pre-training model, and the results obtained prove that our noise reduction network can greatly improve the image quality and further improve the effect of line maintenance.

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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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Multi-Modal Tracking Using LiDAR and Visual Signals 11

Multi-Modal Tracking Using LiDAR and Visual Signals

引用

11th International conference on Electrical Engineering, Computer Science and Informatics, EECSI 2024

作者： Kumar, Sanjay Hassan, Mohamed Escudero-Vinolo, Marcos Hannan, Abdul Manzoor, Anam Godinho, Antonio Pires, Ivan Miguel Coelho, Paulo Jorge Autonomous University of Madrid Madrid Spain University of Bordeaux Bordeaux France University of Management and Technology Punjab Pakistan Polytechnic Institute of Coimbra Technology and Management School of Oliveira Do Hospital Oliveira Do Hospital Portugal Research Center for Arts and Communication Santarém Polytechnic University Santarém Portugal Instituto de Telecomunicações Escola Superior de Tecnologia e Gestião de Agueda Universidade de Aveiro Agueda Portugal School of Technology and Management Polytechnic University of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra Coimbra Portugal

ISBN: (纸本)9798350355314

Multi-object tracking (MOT) is a crucial technique for detecting and tracking multiple objects over time in a scene. It involves locating objects in consecutive frames of a video or sequential observations and establishing correspondences to maintain their identity. MOT is essential in various applications, including autonomous vehicles, robotics, and video surveillance. In autonomous vehicles, it is typically performed using 3D models (LiDAR/stereo) or 2D models (one or more RGB cameras). The LiDAR 3D point-cloud provides a 360-degree view of its surroundings but has a low resolution compared to the camera's visual signals. This paper presents a sensor fusion approach for multi-object detection and tracking, combining object detection information from sensors, LiDAR, and cameras and applying data association algorithms like Hungarian algorithms for tracking to increase the overall system. The EagerMOT approach for 3D Multi-Object Tracking via Sensor Fusion achieves state-of-the-art results across several MOT tasks on the KITTI dataset, achieving an accuracy of 87.95 %. © 2024 IEEE.

关键词： Stereo image processing

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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...

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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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Enhanced DSP Blocks for Full High-Definition Video Bridging Application on FPGAs

Enhanced DSP Blocks for Full High-Definition Video Bridging ...

引用

International conference on Communications, Circuits and systems (ICCCAS)

作者： Panfeng Wang Yici Cai Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798350386271

ISBN: (纸本)9798350386288

FPGA chips are widely used in video bridging applications. The DSP (Digital Signal processing) in FPGA can effectively improve the efficiency of video image processing algorithms. The 10 bits of pixel depth is common for Full High-Definition (FHD). However, in the existing commercial FPGAs, the DSP does not naturally support 10x10 multiplication. This brings some waste in area and power consumption. This paper proposes a new architecture of embedded DSP. It increases the maximum number of 10x10 multiplications in a DSP block to 8. It is also compatible with common working modes such as multiplication (18x18, 18x9), and accumulation. Meanwhile, introduce power gate and clock gate units in the DSP block to achieve fine-grained control of the power consumption. Users can dynamically control the power supply through their own logic. The entire circuit was successfully designed and implemented in an industrial 22nm process. The experimental results show that the static power consumption of the DSP block is about 20uW, the dynamic power consumption is about 200uW. And the maximum operating frequency can reach 670MHz. The effective area utilization of our DSP in 10x10 mode is 2.2 and 2.5 times higher than that in Intel Arria 10 series and xilinx UltraScale series FPGAs, respectively.

关键词： Power demand Circuits and systems image processing Signal processing algorithms Digital signal processing Logic gates Logic

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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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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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Smart Oral Health Monitor

Smart Oral Health Monitor

引用

Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), International conference

作者： Spandana Anilkumar Kamkar Srushti Sanjay Vaishnavi P S Karthik S Dept. of Computer Science and Engineering BNM Institute of Technology Affiliated to VTU Bangalore India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

Oral health is vital to overall well-being but is often overlooked due to inefficient monitoring tools and delayed diagnosis. This project presents a smart handheld device featuring a miniaturized camera for detecting oral issues like plaque, cavities, teeth discoloration and gum diseases in real-time. Using image processing and deep learning algorithms, the device provides precise feedback and actionable insights. Paired with a mobile application offering detailed analysis and recommendations, it empowers users to adopt proactive oral hygiene practices to prevent teeth disorder.

关键词： Deep learning image processing Teeth Cameras Real-time systems Mobile applications Monitoring Diseases

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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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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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