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检索条件"任意字段=Conference on Algorithms, Devices, and Systems for Optical Information Processing"

共 3212 条记录，以下是491-500 订阅

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Research on Infrared Sequence Image Denoising Based on Multiframe Averaging and Improved Bilateral Filtering

Research on Infrared Sequence Image Denoising Based on Multi...

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2021 International conference on optical Instruments and Technology: Optoelectronic Imaging/Spectroscopy and Signal processing Technology

作者： Wang, Huaqiang Shi, Junsheng Zhang, Huaping Xiong, Bingyi Liang, Jing School of Physics and Electronic Information Yunnan Normal University Kunming China Yunnan Key Laboratory of Opto-electronic Information Technology Kunming China

ISBN: (纸本)9781510655676

Infrared imaging systems have been widely used in military and civil fields. However, the degradation of imaging quality is constantly affected by stripe noises. The traditional mean filtering, median filtering, Gaussian filtering, Wiener filtering and other algorithms have dependence on different noise images, and the image edge is blurred by denoising. The popular bilateral filter takes a lot of calculation due to a two-dimension way and floating point spatial proximity factor. In this paper, an infrared sequence image denoising method based on multi-frame averaging and improved bilateral filtering is introduced. An improved bilateral filter with an integer spatial proximity factor is designed, which is realized by one dimension filtering in horizontal and vertical directions. First, basal stripe in each frame image is removed by two-point correction, and the improved bilateral filter is used to smooth the noise and protect the edge of the image at the same time. Second, random noise is further removed by averaging multi-frame with a set of 25 images. The experimental results show that the proposed denoising method can effectively remove the noise and better maintain the edge structural information of the image. © 2022 SPIE.

关键词： Image denoising

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Construction and Research of Automotive Internationalization Platform Based on Spark Distributed System

Construction and Research of Automotive Internationalization...

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Electronics and devices, Computational Science (ICEDCS), International conference on

作者： Cheng Meilin Zhao Sixu Ding Qian China Automotive Technology and Research Center Co. Ltd. Tianjin China China Auto Information Technology (Tianjin) Co. Ltd. Tianjin China

ISBN: (数字)9798331527624

ISBN: (纸本)9798331527631

This paper combines Spark's distributed computing capabilities with CNN's image recognition advantages to improve the transaction efficiency and user experience of the platform. First, this paper uses Spark distributed system to build a platform capable of processing large-scale auto transaction data. Spark's in-memory computing and task scheduling mechanism greatly improves the data processing speed and ensures the real-time and accuracy of transactions. Secondly, by improving the CNN algorithm, the intelligent recognition and classification of car pictures are realized, which not only optimizes the user search experience, but also provides the platform with accurate vehicle information matching capability. Finally, through detailed system simulation, the proposed scheme is verified to improve data processing performance, optimize transaction flow, and enhance user experience. The research results of this paper not only provide a new technical perspective for the construction of the automobile international platform, but also open a new way for the intelligent development of the automobile trading market. Through the fusion application of Spark and CNN, it shows the great potential of distributed computing and deep learning in solving complex transaction scenarios, and provides a valuable reference for the upgrading and optimization of future automotive trading platforms.

关键词： Accuracy Image recognition Data processing User experience Real-time systems Classification algorithms systems simulation Automobiles Sparks Automotive engineering

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Overview of the DJI ZENMUSE L1 Laser Scanner for Spatial Planning Purposes 1

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2nd International Scientific and Practical conference on Digital and information Technologies in Economics and Management, DITEM 2022

作者： Gura, Dmitry Berkova, Elizaveta Panyutischeva, Anastasia Zaidi, Monji Mohamed Turk, Gennadiy Kuban State Technological University 2 St. Moskovskaya Krasnodar350072 Russia Department of Electrical Engineering College of Engineering King Khalid University Abha Saudi Arabia -FSM Monastir University Monastir Tunisia Kuban State Agrarian University named after I.T. Trubilina 13 St. Kalinina Krasnodar350044 Russia

ISBN: (数字)9783031309267

ISBN: (纸本)9783031309250

Laser scanning of objects is a modern method for obtaining 2D and 3D models of the surrounding space. During the operation of the devices, a cloud of points with spatial coordinates is created, which ultimately give a three-dimensional image. Three-dimensional scanning of objects allows you to create digital models not only of individual buildings and structures, but also of entire complexes or territories. Laser scanning technology has existed for a long time, the effect of this technology was felt by specialists in various industries only in the last decade. In geodesy, laser scanning serves as a source of data for creating accurate three-dimensional models. By using drones to quickly collect data from a safe distance, it becomes possible to instantly receive up-to-date information that does not require extra costs. LiDAR technology was introduced into the DJI Zenmuse L1 system, thereby creating a payload module that can translate point clouds in real time and collect data to develop a topographic map of the area. The technology for processing laser scanning data is considered using the DJI ZENMUSE L1 laser scanner as an example. Methods and technologies for processing scanning data at all stages have been collected and combined - from the preliminary processing of "raw data" to the creation of digital elevation models, contour lines and other products. The functionality of DJI Terra and Spatix/Terrascan programs is described. The aim of the study is to study the principles of laser scanning data processing. The research problem is the imperfection of laser scanning data processing methods. As a result of the work done, using the DJI Terra program, the data obtained using the 3D airborne laser scanning technology was processed. With active LiDAR detection, Zenmuse L1 can scan terrain to collect point clouds even at night or in low light conditions with an integrated RGB camera and a high-precision IMU. © 2023, The Author(s), under exclusive license to Springer Nat

关键词： optical radar

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ROUTESENSE – An AI powered solution to Car pooling systems

ROUTESENSE – An AI powered solution to Car pooling systems

引用

International conference on Communications and Signal processing

作者： K Poornimathi A Deepak Kumar A Srinithi Department of Computer science and business systems Rajalakshmi Engineering College

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

Revolutionizing the urban commuting by introducing a ground-breaking AI-powered carpooling portal. This comprehensive platform provides an ultimate solution combining all the latest technologies for transportation challenges. The system ensures effortless scalability and real-time synchronization of user profiles, tip histories and route information across devices. Using the integration of emerging technologies such as Artificial intelligence and Machine learning algorithms, commuters are given a unique advantage of having a seamless travel and an optimized cost for the travel using AI and ML models and they are matched based on their preferences, schedules and historical data that makes the travel more convenient. The system also provides enhanced route security by analyzing the geospatial information to suggest the safest and most efficient routes for carpooling groups. It also streamlines the billing process by introducing Robotic process automation (RPA), ensuring accurate and tamper-free billing process for the carpooling groups. This combination of different technologies makes carpooling into a sophisticated, seamless and efficient mode of sustainable transportation that also is secure while delivering unparalleled convenience and peace of mind to its users.

关键词： Schedules Scalability Transportation Signal processing Data models Real-time systems Synchronization

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Autonomous, Connected and AI-embedded Multi-Sensor System for Wildlife Monitoring

Autonomous, Connected and AI-embedded Multi-Sensor System fo...

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Smart systems Integration (SSI)

作者： Paul Fourcade Esteban Cabanillas Sébastien Brulais CEA-Leti DSYS/SSCE/LAIC Grenoble France

ISBN: (数字)9798350388770

ISBN: (纸本)9798350388787

The rapid expansion of human activities is significantly altering wilderness areas and their biodiversity, resulting in shifts in wildlife populations and highlighting the urgent need to implement automated species tracking systems to monitor environmental health. Current devices in all categories face real limitations, particularly the lack of local information processing, resulting in a passive system that is unable to propose an appropriate response depending on the observed event. This work presents an innovative sensing system including a new architecture for the control and computation unit, combined with a multi-sensor detection mechanism using audio analysis to improve both the device autonomy and reliability. The concept was successfully implemented in a camera trap prototype and deployed in a natural area for several months, collecting many audio and video samples that were highly valuable for training the AI classification model and experimenting with the audio analysis algorithms.

关键词： Training Face recognition Wildlife Prototypes information processing Smart systems Sensors Reliability Biomedical monitoring Monitoring

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Research and analysis of pruning algorithm

Research and analysis of pruning algorithm

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2022 International conference on algorithms, Microchips and Network Applications

作者： Jin, Xin Ma, Xuanmin Tao, Li College of Communication and Information Technology Nanjing University of Posts and Telecommunications Nanjing210023 China Leicester International Institute Dalian University of Technology Panjin124221 China College of Computer Science Sichuan University Chengdu610207 China

ISBN: (纸本)9781510653290

In recent years, thanks to the development of GPU (Graphic processing Unit) computing power, deep neural network (DNN) has drawn extensive attention from academia and industry and has been widely used in various fields of artificial intelligence. However, the mainstream deep learning models have some problems such as large storage space consumption and high computational complexity, which makes it difficult for the deep neural network model to be deployed to mobile devices with limited computing resources or applications with strict delay requirements. Therefore, on the premise of minimizing the loss of model accuracy, the algorithm researches of deep neural network compression and acceleration which can lighten the model has been carried out. In recent years, model compression methods such as pruning, quantification and knowledge distillation have emerged. This paper focuses on neural network pruning algorithm. Firstly, this paper expounds the basic methods and classification of neural network pruning algorithms. Then according to the classification of pruning granularity, a more detailed classification, analysis and comparison of specific models are carried out from the algorithm level. Then based on cifar-10 data set, validity tests of some neural network pruning algorithms and contrastive analyses of the experimental data from different models such as the parameters are carried out. Finally, in combination of the recent results of neural network pruning algorithm, we put forward research dilemmas and problems to be solved. Then the future research trends and methods of neural network pruning algorithm are prospected. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Deep neural networks

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A Comparative Study of Gait Analysis Technologies 13

A Comparative Study of Gait Analysis Technologies

引用

13th International conference on Indoor Positioning and Indoor Navigation, IPIN 2023

作者： Ruiz-Ruiz, Luisa Seco, Fernando Jimenez-Ruiz, Antonio R. Alecto, Evelyn Jimenez-Martin, Ana Garcia-Dominguez, Juan Jesus CSIC-UPM. Ctra. Campo Real km 0.2 Arganda del Rey28500 Spain Universidad de Alcalá Departamento de Electrónica Eps Campus Univer. Alcalá de Henares Spain

ISBN: (纸本)9798350320114

Gait analysis is the systematic study of the movement of human locomotion. It has applications in the field of health by allowing the diagnosis of diseases related to gait disturbances, such as the risk of falling or frailty in the elderly. The identification of these pathologies is carried out by analyzing different specific gait parameters, such as speed, time or length of each step, etc. Currently, there are numerous methods or technologies for gait analysis, mainly divided into non-portable systems (optical systems or pressure mapping corridors) and portable systems (inertial sensors, pressure insoles, electromyography, etc.), with different characteristics and limitations. It is important to be able to assess which technique is the most appropriate to use for each type of gait analysis required. In this work, we study and compare three different technologies for gait analysis, two of them commercial: an optical system (optitrack) and a pressure mapping system for human gait analysis (StrideWay);and a dual inertial system to be placed on the feet (IMUE-CSIC, proprietary design). We analyze the main features of each system, as well as their advantages and limitations, including the gait parameters that they can provide directly or indirectly from the recorded information. In addition, gait trials have been carried out using all three systems simultaneously. The results obtained reveal very small differences between them, being less than 0.02 seconds for gait cycle time and 0.03 meters for stride length. The advantages of using IMUs are their low cost and portability (allowing outdoor testing). Despite requiring complex post-processing algorithms, they provide a broad set of gait parameters. The optical system and the pressure mapping corridor for human gait analysis have high resolution, but their high cost and lack of portability make them difficult to use in real conditions outside the laboratory. Additionally, the pressure corridor provides more extensive resu

关键词： Gait Analysis Inertial Sensor optical System Pressure Sensor

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Research and implementation of unified management method for power distribution and distributed new energy data resources 3

Research and implementation of unified management method for...

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3rd International conference on Electronics, Electrical and information Engineering, ICEEIE 2023

作者： Qiao, Junfeng Zhou, Aihua Peng, Lin Shen, Xiaofeng Chen, Jingde Gu, Hua State Grid Laboratory of Power cyber-Security Protection & Monitoring Technology State Grid Smart Grid Research Institute Co.LTD Jiangsu Nanjing210003 China Qingpu Power Supply Company State Grid Shanghai Municipal Electric Power Company Shanghai201799 China

ISBN: (纸本)9781510671423

The physical types of equipment in the distribution network are diverse and the quantity is huge. This is because the distribution network requires a large number of various types of power supply and other auxiliary equipment such as substations to provide power supply services for electricity customers, resulting in a very rich and diverse data resources in the distribution network. Moreover, with the continuous integration of new energy sources, the distribution network has become increasingly complex, not only increasing the dimensions of operational management, but also facing huge challenges in data resource management. This paper proposes a unified management method for power distribution and new energy data resources, which manages a large number of non digital data and unstructured data such as file text in the distribution network in a unified manner, integrates heterogeneous data from different business systems, solves data quality problems caused by management, data processing and other reasons, meets the data management needs of power grid enterprises, and promotes Digital transformation of enterprises. On the basis of achieving unified management of data resources in the distribution network, the deep mechanisms between data resources are explored to reveal the operational laws and characteristics of the distribution network. At the same time, data analysis algorithms are used to mine distribution network data, design and implement distribution network business analysis functional modules, and upgrade distribution network data management from digitalization to intelligence. © 2023 SPIE.

关键词： information management

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Development and Characterization of a Hyperspectral LCTF-based Colposcopic System

Development and Characterization of a Hyperspectral LCTF-bas...

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conference on Liquid Crystals Optics and Photonic devices

作者： Vega, Carlos Marquez-Suarez, Nerea Leon, Raquel Castro-Femandez, Maria Socorro-Marrero, Guillermo, V Fabelo, Himar Rial-Ferrario, Jorge Callico, Gustavo M. Univ Las Palmas de Gran Canaria ULPGC Inst Appl Microelect IUMA Las Palmas Gran Canaria Spain Fdn Inst Invest Sanitaria Canarias FIISC Las Palmas Gran Canaria Spain OPTOMIC Espana SA Madrid Spain

ISBN: (纸本)9781510673519;9781510673502

The early detection of precancerous cervical lesions is essential to improve patient treatment and prognosis. Hyperspectral (HS) imaging (HSI) has demonstrated a high potential to become a new non-invasive and label-free imaging technique in the medical field for performing quick diagnosis of different diseases. This study presents the research and development process to integrate and characterize a KURIOS-XE2 filter (Thorlabs, Inc., NJ, USA), based in a liquid crystal tunable filter (LCTF) technology, into an existing colposcope (C5, OPTOMIC, Spain). The main goal was to capture spectral information in the near infrared range (650-1100 nm) by using a monochrome camera and acquiring 90 spectral wavelengths with a spectral resolution of 5 nm. Two different integration strategies were studied: i) filtering the emitted light by the sensor and ii) filtering the received light by the sensor, evaluating their respective benefits and limitations. Furthermore, a custom software was developed for HS image acquisition, integrating a variable acquisition time per wavelength, which allows improving the signal-to-noise ratio at wavelengths where the system presents lower quantum efficiency. The proposed system simplifies the adaptation of existing optical systems to HSI technology, improving the signal-to-noise ratio in the studied spectral range respect to other approaches. The results were compared against a previous custom implementation based on a Snapscan camera (IMEC, Belgium), covering the visual and near infrared and highlighting the advantages and limitations of both technologies for the development of a HS colposcope system targeting early detection of precancerous cervical lesions during routine clinical practice.

关键词： Hyperspectral imaging liquid crystal tunable filter cervical cancer image processing medical imaging medical instrumentation colposcopy

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Classifying Cognitive Workload Using Machine Learning Techniques and Non-Intrusive Wearable devices

Classifying Cognitive Workload Using Machine Learning Techni...

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IEEE International conference on Human-Machine systems

作者： Yunmei Liu Nicolas S. Grimaldi Niosh Basnet David Wozniak Eric Chen Maryam Zahabi David Kaber Jaime Ruiz Department of Industrial Engineering University of Louisville Louisville KY USA Department of Industrial & Systems Engineering University of Florida Gainesville FL USA Department of Industrial & Systems Engineering Wm Michael Barnes ’64 Texas A&M University College Station TX USA Department of Computer & Information Science & Engineering University of Florida Gainesville FL USA

ISBN: (数字)9798350315790

ISBN: (纸本)9798350315806

Effective management of cognitive workload is essential to ensure user performance and minimize mental fatigue. This study aimed to evaluate the effectiveness of three machine learning (ML) algorithms, including a Support Vector Machine (SVM), a Random Forest (RF) and Random Fourier Features (RFF) models, for predicting instances of high cognitive workload based on physiological data collected from non-intrusive wearable devices. The study included scenarios to induce high workload. After processing data from 30 human participants, and extracting cognitive workload-related features, we evaluated the ML algorithms in terms of accuracy, Area Under the Curve (AUC), and Average Precision (AP) responses. The RFF model emerged as a top performer, achieving 97% accuracy, 99.5% AUC, and 99% AP, demonstrating the capability to detect high workload scenarios and robustness to unbalanced data in workload predictions. The most significant physiological features in the RFF model included skin conductance level (SCL) change, SCL mean, and percent change in pupil size. Future studies should enhance the present binary classification model to support multi-class or continuous workload predictions and implement real-time analysis using trained algorithms.

关键词： Support vector machines Performance evaluation Machine learning algorithms Accuracy Predictive models Prediction algorithms Feature extraction

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