The three-volume set CCIS 761, CCIS 762, and CCIS 763 constitutes the thoroughly refereed proceedings of the International conference on Life System Modeling and Simulation, LSMS 2017, and of the International Confere...
ISBN:
(数字)9789811063640
ISBN:
(纸本)9789811063633
The three-volume set CCIS 761, CCIS 762, and CCIS 763 constitutes the thoroughly refereed proceedings of the International conference on Life System Modeling and Simulation, LSMS 2017, and of the International conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017, held in Nanjing, China, in September 2017. The 208 revised full papers presented were carefully reviewed and selected from over 625 submissions. The papers of this volume are organized in topical sections on: Biomedical Signal processing; Computational Methods in Organism Modeling; Medical Apparatus and Clinical Applications; Bionics Control Methods, algorithms and Apparatus; Modeling and Simulation of Life systems; Data Driven Analysis; image and Video processing; Advanced Fuzzy and Neural Network Theory and algorithms; Advanced Evolutionary Methods and Applications; Advanced Machine Learning Methods and Applications; Intelligent Modeling, Monitoring, and Control of Complex Nonlinear systems; Advanced Methods for Networked systems; Control and Analysis of Transportation systems; Advanced Sliding Mode Control and Applications; Advanced Analysis of New Materials and Devices; Computational Intelligence in Utilization of Clean and Renewable Energy Resources; Intelligent Methods for Energy Saving and Pollution Reduction; Intelligent Methods in Developing Electric Vehicles, Engines and Equipment; Intelligent Computing and Control in Power systems; Modeling, Simulation and Control in Smart Grid and Microgrid; Optimization Methods; Computational Methods for Sustainable Environment.
Prostate cancer is becoming a threat to humanity. Today, the diagnosis of diseases is still be realized mostly by manual methods. Nevertheless, this traditional process is inefficient and not accurate. Its precision d...
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ISBN:
(纸本)9781538631751
Prostate cancer is becoming a threat to humanity. Today, the diagnosis of diseases is still be realized mostly by manual methods. Nevertheless, this traditional process is inefficient and not accurate. Its precision depends on the operator's expertise. Thus, applying machine learning algorithms for malignant cells detection and counting remains a significant purpose in medical image analysis research. In this paper, we apply a modified ACO algorithm to measure the rate of cell growth of cancer's patient automatically due to segmentation and counting process. The proposed method was applied on several medical images obtained from MRI-guided prostate biopsies. The robustness of this idea was showed by comparison with hand-labeled obtained segmentation results.
Nowadays, the individuals identification is a problem in many private company, but also in governmental and public order entities. Currently, there are multiple biometric methods, each with different advantages. A mod...
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ISBN:
(纸本)9781538692349;9781538692332
Nowadays, the individuals identification is a problem in many private company, but also in governmental and public order entities. Currently, there are multiple biometric methods, each with different advantages. A modern biometric method, which has several advantages, especially in terms of security against forgery, is finger vein identification. In the present work we have proposed and developed multi-core algorithms for the identification of people using finger veins, based on the SIFT displacement method, which currently has reached the highest efficiency performance in the state-of-the-art in the finger vein identification. The highest performance was reached with the hierarchical multi-core version, which uses two different type of threads, one is in charge of the query management and the second one in charge of the query processing with the database.
Quantitative acoustic microscopy (QAM) is an imaging modality which uses very-high-frequency ultrasound (i.e., >200 MHz) to form two-dimensional (2D) quantitative images of acoustical and mechanical properties of s...
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ISBN:
(纸本)9781509041176
Quantitative acoustic microscopy (QAM) is an imaging modality which uses very-high-frequency ultrasound (i.e., >200 MHz) to form two-dimensional (2D) quantitative images of acoustical and mechanical properties of soft tissues with microscopic resolution (i.e., better than 8 mu m). The key component of a QAM system is the ultrasound transducer which must be broadband, have a very small F-number (i.e., < 1.2), and good sensitivity. In this study, two QAM systems based on a 250-MHz and a 500-MHz transducer are presented, yielding 2D quantitative images at spatial resolution of 7 mu m and 4 mu m respectively. Thin tissue sections obtained using a microtome or cryotome are raster scanned with precise motors and pulse-echo RF signals are digitized. Inverse models are then used to process each RF signal individually to estimate acoustic impedance, speed of sound, and acoustic attenuation as well as derived parameters such as bulk modulus, mass density, and compressibility. To illustrate the QAM technology and signal processingalgorithms, images from cancerous human lymph nodes and ophthalmologic samples are presented and coregistered with histology photomicrographs.
Realization of automated reading and video processing to study efficient algorithms for tracking the dynamics of growth and spread of spores of mesophilic and thermophilic microorganisms were studied. The basic steps ...
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ISBN:
(纸本)9781538606971
Realization of automated reading and video processing to study efficient algorithms for tracking the dynamics of growth and spread of spores of mesophilic and thermophilic microorganisms were studied. The basic steps based on the algorithm of automatic counting and tracking spore colonies in real time were investigated.
This paper introduces DUBIO, a cloud platform which analyzes the radiometric infrared videos uploaded by drones which patrol large PV plants. Thanks to its artificial vision algorithms, DUBIO does not require any huma...
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This paper introduces DUBIO, a cloud platform which analyzes the radiometric infrared videos uploaded by drones which patrol large PV plants. Thanks to its artificial vision algorithms, DUBIO does not require any human intervention in selecting and associating the framed PV modules to the corresponding ones in the topology of the plant. DUBIO implements an innovative diagnostic protocol, which evidences the behavior of the module independently from the environmental conditions, i.e., decontextualizes the overheating of each module from the external conditions. By this way, the data automatically computed and collected in a multimedia database provide the O&M technicians with significant information, useful also for studying the ageing trend of each module of the monitored plant. The system, which is currently under a massive test in several plants of Enel Green Power, will constitute a pay for use service cloud platform worldwide available to the O&M market, since the second quarter of 2018.
This paper presents an analysis of code implementation performance for imageprocessingalgorithms. The test is made for imageprocessingalgorithms for robotic arms, but it is suitable for any type of image processin...
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This paper presents an analysis of code implementation performance for imageprocessingalgorithms. The test is made for imageprocessingalgorithms for robotic arms, but it is suitable for any type of imageprocessing software. imageprocessing software can use quite big amount of resources, so this way it can be tested which platform, which operating system or which programming language is the most suitable for usage. The imageprocessing task is a color detection task with some line and circle overlays for robotic arm's guidance. The implementations were tested base on code line numbers, code size on disk, binary file size on disk, used memory during execution and used CPU during execution.
Interest point detection is one of the key technologies in imageprocessing and target recognition. This paper presents a new method for detecting interest points in digital images and computer vision problems based o...
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ISBN:
(纸本)9781538629185
Interest point detection is one of the key technologies in imageprocessing and target recognition. This paper presents a new method for detecting interest points in digital images and computer vision problems based on complex network theory. We associate a directed and weighted complex network model to each image and then we propose three different algorithms to locate these key points based on three topological features of image complex network model, which are degree, closeness and betweenness.
One of the most important tasks being solvable on the aircraft board is a task of imposition of real images and images synthesized according to the digital terrain map. Complex of auxiliary tasks and actual imposition...
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One of the most important tasks being solvable on the aircraft board is a task of imposition of real images and images synthesized according to the digital terrain map. Complex of auxiliary tasks and actual imposition task should be solved on a real time basis (with frequency 25 frames per second) and with strict requirements to accuracy of the heterogeneous image imposition. Traditional correlation-extremal methods of imposition ensure a necessary accuracy but require unacceptably high expenditures of computer time. The paper describes an algorithm of imposition based on affine transformations of the synthesized image to the plane of a real video image and also algorithms for solution of auxiliary tasks.
In this paper, we present a novel denoising algorithm based on the Rodin-Osher-Fatemi (ROF) model. The goal is to ensure maximum noise removal while preserving image details. To achieve this goal, we developed a new e...
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