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

共 15578 条记录，以下是4781-4790 订阅

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Testbed for thermal imager characterization using an infrared scene projector 15

Testbed for thermal imager characterization using an infrare...

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conference on Electro-Optical and Infrared systems - Technology and Applications XV

作者： Koerber, Michael Wegner, Daniel Schwarz, Bastian Ritt, Gunnar Kessler, Stefan Eberle, Bernd Fraunhofer IOSB D-76275 Ettlingen Germany

ISBN: (数字)9781510621749

ISBN: (纸本)9781510621749

Based on previous work on thermal imager performance analysis at Fraunhofer IOSB using specific scenes and patterns, we present our advances in setting up a testbed for thermal imager characterization with a MIRAGE (TM) XL infrared scene projector. In the first part, we outline the experimental setup of our testbed. It allows for mimicking infrared imaging of real scenes in a controlled laboratory environment. We describe the process of dynamic infrared scene generation as well as the physical limitations of our scene projection setup. A second part discusses ongoing and future applications. This testbed extends our standard lab measurements for thermal imagers by a image based performance analysis method. Scene based methods are necessary to investigate and assess advanced digital signal processing (ADSP) algorithms which are becoming an integral part of thermal imagers. We use this testbed to look into inferences of unknown proprietary ADSP algorithms by choosing suitable test scenes. Furthermore, we investigate the influence of dazzling on thermal imagers by coupling infrared laser radiation into the projected scene. The studies allow to evaluate the potential and hazards of infrared dazzling and to describe correlated effects. In a future step, we want to transfer our knowledge of viS/NIR laser protection into the infrared regime.

关键词： IR scene generator IR scene projector image based performance thermal imager characterization laser dazzle

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A Microservice-Based Building Block Approach for Scientific Workflow Engines: processing Large Data Volumes with DagOnStar

A Microservice-Based Building Block Approach for Scientific ...

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International IEEE conference on Signal-image Technologies and Internet-Based System

作者： Dante D. Sánchez-Gallegos Diana Di Luccio J. L. Gonzalez-Compean Raffaele Montella Cinvestav Ciudad Victoria Mexico Dpt. of Science and Technologies University of Naples "Parthenope" Naples Italy Unidad Tamaulipas Cinvestav Victoria Mexico

ISBN: (数字)9781728156866

ISBN: (纸本)9781728156873

The impact of machine learning algorithms on everyday life is overwhelming until the novel concept of datacracy as a new social paradigm. In the field of computational environmental science and, in particular, of applications of large data science proof of concept on the natural resources management this kind of approaches could make the difference between species surviving to potential extinction and compromised ecological niches. In this scenario, the use of high throughput workflow engines, enabling the management of complex data flows in production is rock solid, as demonstrated by the rise of recent tools as Parsl and DagOnStar. Nevertheless, the availability of dedicated computational resources, although mitigated by the use of cloud computing technologies, could be a remarkable limitation. In this paper, we present a novel and improved version of DagOnStar, enabling the execution of lightweight but recurring computational tasks on the microservice architecture. We present our preliminary results motivating our choices supported by some evaluations and a real-world use case.

关键词： Task analysis Engines Cloud computing Containers Tools Architecture Prototypes

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GPU Cuda JSEG Segmentation Algorithm associated with Deep Learning Classifier for Electrical Network images Identification 22

GPU Cuda JSEG Segmentation Algorithm associated with Deep Le...

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22nd International conference on Knowledge-Based and Intelligent Information and Engineering systems (KES)

作者： Fambrini, Francisco Iano, Yuzo Caetano, Diogo Gara Rodriguez, Abel A. D. Moya, Clodoaldo Carrara, Eduardo Arthur, Rangel Cabello, Frank C. Von Zubem, Joao Del Val Cura, Luis Mariano Destro-Filho, Joao Batista Campos, Jose Roberto Saito, Jose Hiroki Univ Fed Sao Carlos BR-13565905 Sao Carlos Brazil Univ Estadual Campinas UNICAMP BR-13083970 Campinas Brazil UNIFACCAMP Campo Limpo Paulista Brazil Univ Fed Uberlandia BR-38400902 Uberlandia MG Brazil

An automatic recognizer system based in Artificial Intelligence for thermographic images of the electric power distribution network is proposed in this article. The infrared thermography is usually used to conduct inspections in electrical power distribution lines, assisted by a human operator, which is usually responsible for operating all the equipment, selecting the hottest spots in the image (corresponding to the places needing maintenance), making reports and calling the technical team, which will do the repairs. The proposed automatic diagnosis system aims to replace the manual inspection operation using image processing algorithms. An old method of segmentation for thermal images known as JSEG is implemented and tested and a Deep Learning Neural Network is responsible to recognize the segmented elements. A comparison between the exclusive Deep Learning based image recognition with the same method preceded by the JSEG segmentation algorithm is done in this article, showing better performance with this previous segmentation of the thermographic images. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： Thermography image processing Deep Learning CUDA JSEG Segmentation Preventive Maintenance Infrared Photo

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Estimating vital signs through non-contact video-based approaches: A survey

Estimating vital signs through non-contact video-based appro...

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2017 International conference on Recent Innovations in Signal processing and Embedded systems, RISE 2017

作者： Sinhal, Ruchika Singh, Kavita Shankar, Anuraj Department of CSE DMIETR Wardha India Department of CT YCCE Nagpur India HSPH Boston United States

ISBN: (纸本)9781509047604

The human body exhibits many vital signs, such as heart rate (HR) and respiratory rate (RR) used to assess fitness and health. vital signs are typically measured by a trained health professional and may be difficult for individuals to accurately measure at home. Clinic visits are therefore needed with associated burdens of cost and time spent waiting in long queues. The widespread use of smart phones with video capability presents an opportunity to create non-invasive applications for assessment of vital signs. Over the past decade, several researchers have worked on assessing vital signs from video, including HR, RR and other parameters such as anemia and blood oxygen saturation (SpO2). This paper reviews the different image and video processing algorithms developed for vital signs assessment through non-contact methods, and outline the key remaining challenges in the field which can be used as potential research topics. The CHROM algorithm produces highest accuracy in detecting the signals from rPPG. There are different challenges of handling large database and motion stabilization which is not provided by any algorithm, this is main area of research in rPPG. © 2017 IEEE.

关键词： video signal processing

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Shape and Relief Evaluation Using the Light Field Camera

Shape and Relief Evaluation Using the Light Field Camera

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International conference on Innovations and Prospects of Development of Mining Machinery and Electrical Engineering, IPDME 2018

作者： Makhov, V.E. Sytko, I.I. Mozhaisky Military Space Academy Zhdanov Street 13 St. Petersburg197082 Russia Saint Petersburg Mining University 21 Line St. Petersburg199106 Russia

The paper considers an optical system for controlling the shape and micro-relief of products using a single-camera optoelectronic light field recorder. Based on National Instruments computer technologies, image processing algorithms and basic surface measurements have been developed. To accurately determine macro- and micro-relief parameters the authors propose algorithms for morphological analysis of two images obtained from a multi-focus light field file at a given depth of field. It is shown that the method of capturing the light field makes it possible to obtain the accuracy of surface relief by the height of its profile compared to other methods, while significantly reducing control requirements. © Published under licence by IOP Publishing Ltd.

关键词： Optical systems

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Machine learning and digital image processing for non-contact modal parameters identification of structures

Machine learning and digital image processing for non-contac...

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conference on Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace systems

作者： Torbol, M. Park, K. T. Ulsan Natl Inst Sci & Technol 50 UNIST Gil Ulsan 44919 South Korea

ISBN: (数字)9781510616936

ISBN: (纸本)9781510616936

This study introduces an innovative non-contact sensing technique for vision-based displacement measurement. Existing vision-based displacement measurement techniques utilizes physical target panels or physical features to compute relative displacement between the target and the observation point. Instead, the proposed method exploits the optical reference of a speckle pattern. A coherent light that is diffusely reflected on the surface of the target structure creates the speckle pattern. In this study, a camera records the changes in the speckle pattern in real time. Because the speckle pattern is sensitive to small changes of surface, the ambient vibration is enough to affect it. To estimate the displacement of the target from the raw speckle images, speckle contrast imaging (SCI), speckle flow imaging (SFI), and k-means clustering algorithm were used. After SCI and SFI quantifies the blurring effect in each image, the k-means clustering algorithm creates virtual sensing node from each image. The connection of virtual nodes from frame to frame highlights the displacements of the surface in time domain. Because the algorithms are time-consuming and computationally intensive, a GPU executes the entire post-processing operation in parallel and identifies the natural frequencies of the structure.

关键词： GPGPU computing CUDA C speckle pattern modal identification

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Big Data Analysis and Deep Learning Applications: Proceedings of the First International conference on Big Data Analysis and Deep Learning

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2018年

作者： Thithi Zin Jerry Chun Wei Lin

ISBN: (纸本)9789811308680

This book presents a compilation of selected papers from the first International conference on Big Data Analysis and Deep Learning Applications (ICBDL 2018), and focuses on novel techniques in the fields of big data analysis, machine learning, system monitoring, image processing, conventional neural networks, communication, industrial information, and their applications. Readers will find insights to help them realize more efficient algorithms and systems used in real-life applications and contexts, making the book an essential reference guide for academic researchers, professionals, software engineers in the industry, and regulators of aviation authorities.

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FFT-Based Deep Learning Deployment in Embedded systems

FFT-Based Deep Learning Deployment in Embedded Systems

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Design, Automation and Test in Europe conference and Exhibition (DATE)

作者： Lin, Sheng Liu, Ning Nazemi, Mandi Li, Hongjia Ding, Caiwen Wang, Yanzhi Pedram, Massoud Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA Univ Southern Calif Dept Elect Engn Los Angeles CA USA

ISBN: (纸本)9783981926309

Deep learning has delivered its powerfulness in many application domains, especially in image and speech recognition. As the backbone of deep learning, deep neural networks (DNNs) consist of multiple layers of various types with hundreds to thousands of neurons. Embedded platforms are now becoming essential for deep learning deployment due to their portability, versatility, and energy efficiency. The large model size of DNNs, while providing excellent accuracy, also burdens the embedded platforms with intensive computation and storage. Researchers have investigated on reducing DNN model size with negligible accuracy loss. This work proposes a Fast Fourier Transform (FFT)-based DNN training and inference model suitable for embedded platforms with reduced asymptotic complexity of both computation and storage, making our approach distinguished from existing approaches. We develop the training and inference algorithms based on FFT as the computing kernel and deploy the FFT-based inference model on embedded platforms achieving extraordinary processing speed.

关键词： Computational modeling Machine learning Training Inference algorithms Feature extraction Embedded systems Neurons

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A System for Automatic Town Sign Recognition for Driver Assistance systems

A System for Automatic Town Sign Recognition for Driver Assi...

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International conference on Computer vision and Graphics (ICCVG)

作者： Frejlichowski, Dariusz Mikolajczak, Piotr West Pomeranian Univ Technol Fac Comp Sci & Informat Technol Zolnierska 52 PL-71210 Szczecin Poland

ISBN: (纸本)9783030006921;9783030006914

The paper describes two different ways of recognizing the road signs that can be applied to the autonomous driver assistance systems. It provides the road sign content and analysis of implemented algorithms, in order to apply them in such systems, resulting in the extension of their functionalities. The mobile application implemented as part of performed experiments, works using the real-time data. The application has been tested practically-the smartphone placed in a car was registering and analyzing the road signs. The paper describes the possibilities of practical use of a mobile device in combination with a real-time data processing program for the detection and recognition of selected road signs. The theoretical part discusses some important automotive topics and selected methods for road signs analysis. As part of practical section, two different methods of road sign recognition, have been implemented and analyzed. The application has been studied and made for iOS system. The OpenCV library has been additionally used. Also, the possibilities of development and optimization of selected algorithms have been shown.

关键词： Data handling

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A fast and efficient semi-guided algorithm for flat coloring line-arts

A fast and efficient semi-guided algorithm for flat coloring...

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2018 conference on vision, Modeling and visualization, VMV 2018

作者： Fourey, S. Tschumperlé, D. Revoy, D. Normandie Univ. UNICAEN ENSICAEN CNRS Caen France Montauban France

ISBN: (纸本)9783038680727

We present a fast and efficient algorithm for the semi-supervised colorization of line-art images (e.g. hand-made cartoons), based on two successive steps: 1. A geometric analysis of the stroke contours, and their closing by splines/segments, and 2. A colorization step based on the filling of the corresponding connected components, either with random colors or by extrapolating user-defined color scribbles. Our processing technique performs image colorization with a similar quality as previous state of the arts algorithms, while having a lower algorithmic complexity, leading to more possible user interactivity. © 2018 The Author(s) Eurographics Proceedings © 2018 The Eurographics Association.

关键词： Parallel processing systems

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