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

共 12978 条记录，以下是4331-4340 订阅

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Methods and means of 3D diffuse Mueller-matrix tomography of depolarizing optically anisotropic biological layers 40

Methods and means of 3D diffuse Mueller-matrix tomography of...

引用

conference on Applications of Digital image processing XL

作者： Dubolazov, O. V. Ushenko, V. O. Trifonyuk, L. Ushenko, Yu. O. Zhytaryuk, V. G. Prydiy, O. G. Grytsyuk, M. Kushnerik, L. Meglinskiy, I. Chernivtsi Natl Univ 2 Kotsyubinsky Str UA-58012 Chernovtsy Ukraine Bukovinian State Med Univ UA-58000 Chernovtsy Ukraine Univ Oulu POB 4500 Oulu Finland

ISBN: (数字)9781510612501

ISBN: (纸本)9781510612501;9781510612495

A new technique of Mueller-matrix mapping of polycrystalline structure of histological sections of biological tissues is suggested. The algorithms of reconstruction of distribution of parameters of linear and circular birefringence of prostate histological sections are found. The interconnections between such distributions and parameters of linear and circular birefringence of prostate tissue histological sections are defined. The comparative investigations of coordinate distributions of phase anisotropy parameters formed by fibrillar networks of prostate tissues of different pathological states (adenoma and carcinoma) are performed. The values and ranges of change of the statistical (moments of the 1st - 4th order) parameters of coordinate distributions of the value of linear and circular birefringence are defined. The objective criteria of cause of Benign and malignant conditions differentiation are determined.

关键词： polarization Fourier optics and signal processing imaging systems medical and biological imaging

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Tree-Based Vehicle Classification System 14

Tree-Based Vehicle Classification System

引用

2017 14th International conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)

作者： Saripan, Kiatkachorn Nuthong, Chaiwat King Mongkuts Inst Technol Ladkrabang Int Coll Bangkok Thailand

ISBN: (纸本)9781538604496

Nowadays, traffic surveillance systems are installed in major cities. They are usually used for two purposes, i.e. real-time traffic monitoring and archived events searching. For the latter purpose, the traffic surveillance systems can be used for police officers' benefits, such as vehicle identification in specific events including stolen vehicles or hit-and-run cases. In such circumstances, the officers are required to identify the vehicle in archived videos according to its appearances. This task is usually accomplished manually through visual perception. The problems arise from this approach Even though this approach results in good accuracy, it is time consuming and prone to error due to human fatigue for long duration videos. In order to solve these problems, a tree based vehicle classification system is proposed. This system consists of three modules, i.e. feature extraction, classification, and search manager. The feature extraction module is used for image and video processing. It extracts the desired features to be used further in the classification module. The classification module uses these features and results in pre-defined vehicle classes. The classification results are stored in the search manager module for further filtering according to user's query command. This paper focuses on the classification module. There are two features designed to be used in the proposed classification module, i.e. types and colors. Vehicles are classified into four classes of type and seven classes of color. Several tree based algorithms are applied to the dataset. The experimental results show that all the algorithms are comparable. However, the highest accuracy for type and color classification are obtained by using decision tree and bagged decision tree, respectively.

关键词： Decision trees Videos Feature extraction Color Training image color analysis Bagging

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Weed Segmentation from Grayscale Tobacco Seedling images 25th

Weed Segmentation from Grayscale Tobacco Seedling Images

引用

25th International conference on Robotics in Alpe-Adria-Danube Region (RAAD)

作者： Lameski, Petre Zdravevski, Eftim Kulakov, Andrea Univ St Cyril & Methodius Skopje Fac Comp Sci & Engn Skopje North Macedonia

ISBN: (纸本)9783319490588;9783319490571

Manual weed extraction from young seedlings is a hard manual labour process. It has to be continuously performed to increase the yield per land unit of any agricultural product. Precise segmentation of plant images is an important step towards creating a camera sensor for weed detection. In this paper we present a machine learning approach for segmenting weed parts from images. A dataset has been generated using bumblebee camera under various light conditions and subsequently training and test patches were extracted. We have generated various texture-based descriptors and used different classification algorithms aiming at correctly recognizing weed patches. The results show that in a case when the images are grayscale, the light conditions are varying, and the distance of the camera to the weeds is not constant machine learning algorithms perform poorly.

关键词： Weed control image processing Machine learning Precision agriculture

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Proceedings - 2017 International conference on Promising Electronic Technologies, ICPET 2017

Proceedings - 2017 International Conference on Promising Ele...

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2017 International conference on Promising Electronic Technologies, ICPET 2017

ISBN: (纸本)9781538622698

The proceedings contain 25 papers. The topics discussed include: sizing and simulation of an energy sufficient stand-alone PV pumping system;mobile educational workbench for classical and programmable control applications;fuzzy gain scheduling control for a special case of 2nd order non-linear systems;detection and removing cross site scripting vulnerability in PHP web application;mobile-computing based rationalization for energy consumption;design of efficient microstrip linear antenna array for 5G communications systems;and intelligent maze solving robot based on image processing and graph theory algorithms.

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Smart Annotation Tool for Multi-sensor Gait-based Daily Activity Data

Smart Annotation Tool for Multi-sensor Gait-based Daily Acti...

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IEEE International conference on Pervasive Computing and Communications

作者： Christine F. Martindale Nils Roth Julius Hannink Sebastijan Sprager Bjoern M. Eskofier Machine Learning and Data Analytics Lab Computer Science Department Friedrich-Alexander University Erlangen-Nürnberg Germany Faculty of Computer and Information Science University of Ljubljana Slovenia

ISBN: (纸本)9781538632284

The monitoring of patients within a natural, home environment is important in order to close knowledge gaps in the treatment and care of neurodegenerative diseases, such as quantifying the daily fluctuation of Parkinson's patients' symptoms. The combination of machine learning algorithms and wearable sensors for gait analysis is becoming capable of achieving this. However, these algorithms require large, labelled, realistic datasets for training. Most systems used as a ground truth for labelling are restricted to the laboratory environment, as well as being large and expensive. We propose a study design for a realistic activity monitoring dataset, collected with inertial measurement units, pressure insoles and cameras. It is not restricted by a fixed location or capture volume and still enables the labelling of gait phases or, where non-gait movement such as jumping occur: on-the-ground, off-the-ground phases. Additionally, this paper proposes a smart annotation tool which reduces annotation cost by more than 80%. This smart annotation is based on edge detection within the pressure sensor signal. The tool also enables annotators to perform assisted correction of these labels in a post-processing step. This system enables the collection and labelling of large, fairly realistic datasets where 93% of the automatically generated labels are correct and only an additional 10% need to be inserted manually. Our tool and protocol, as a whole, will be useful for efficiently collecting the large datasets needed for training and validation of algorithms capable of cyclic human motion analysis in natural environments.

关键词： image edge detection Tools Cameras Labeling Pressure sensors Intelligent sensors Edge detection Pressure Sensor Device Component Cameras intelligent sensors ANNOTATIONS laboratory environment Dataset Wearable sensors Measurement units Research Design INSOLE Packaging

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ASePPI: Robust Privacy Protection against De-Anonymization attacks 30

ASePPI: Robust Privacy Protection against De-Anonymization a...

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30th IEEE/CVF conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Ruchaud, Natacha Dugelay, Jean-Luc Eurecom 450 Route Chappes Sophia Antipolis France

ISBN: (纸本)9781538607336

The evolution of the video surveillance systems generates questions concerning protection of individual privacy. In this paper, we design ASePPI, an Adaptive Scrambling enabling Privacy Protection and Intelligibility method operating in the H.264/AVC stream with the aim to be robust against de-anonymization attacks targeting the restoration of the original image and the re-identification of people. The proposed approach automatically adapts the level of protection according to the resolution of the region of interest. Compared to existing methods, our framework provides a better trade-off between the privacy protection and the visibility of the scene with robustness against de-anonymization attacks. Moreover, the impact on the source coding stream is negligible.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Evaluating classification algorithms for improved wastewater system calibration 15

Evaluating classification algorithms for improved wastewater...

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15th International conference on Computing and Control for the Water Industry, CCWI 2017

作者： Younis, Mohammed Chachan Keedwell, Edward Savic, Dragan Raine, Anthony Department of Computer Science Centre for Water Systems College of Engineering Physics and Mathematics University of Exeter United Kingdom WEM MCIWEM Pell Frischmann

Hydraulic models provide an approximate model of rainfallcollection (storm), wastewatercollection (foul), and combined (both rainfall and wastewater collections) network performance, capturing the large scale element of the system, but such systems require calibration with real world data to achieve reliable and accurate results. However, many factors surrounding real-world network and catchment characteristics are unknown and can influence the hydraulic performance of the network. Consequently, calibrating wastewater models to accurately reflect real-world conditions is a time consuming and complex process. This paper employs a two stage urban run offforecasting approach with a combination of image classification techniques and modelling using Info Works ICM. The image classification section consists of the automated processing of the satellite image as an aid to modelling wastewater in the urban environment by classifying the land-cover as pervious and impervious segments of water from rainfall events. By classifying such areas with an urban catchment, and by using the Wallingford PR Equation across all testsof Area 1 (roads), 2 (roofs) and 3 (permeable area), we explore the potential for a partially automated network system calibration processof a wastewater network. © 2020 CCWI 2017 - 15th International conference on Computing and Control for the Water Industry. All rights reserved.

关键词： image classification

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Advances in Rough Set Based Hybrid Approaches for Medical image Analysis

Advances in Rough Set Based Hybrid Approaches for Medical Im...

引用

International Joint conference on Rough Sets (IJCRS)

作者： Maji, Pradipta Indian Stat Inst Biomed Imaging & Bioinformat Lab Machine Intelligence Unit 203 BT Rd Kolkata W Bengal India

ISBN: (纸本)9783319608372;9783319608365

Recent advancement in the area of medical imaging produces a huge amount of image data. Automatic extraction of meaningful information from these data has become necessary. In this regard, different image processing techniques provide efficient tools to extract and interpret meaningful information from the medical images, which, in turn, provide valuable directions for medical diagnosis. One of the major problems in real-life medical image data analysis is uncertainty. Among other soft computing techniques, rough sets provide a powerful tool to handle uncertainties, vagueness, and incompleteness associated with data, while fuzzy set and probabilistic paradigm serve as analytical tools for dealing with uncertainty that arises due to the overlapping characteristics and/or randomness in data. Hence, they can be integrated judiciously to develop efficient algorithms for automatic analysis of medical image data. In this regard, the paper presents a brief review on recent advances of rough set based hybrid intelligent approaches for medical image analysis.

关键词： Rough sets Medical imaging Hybrid intelligent systems

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Schedulability analysis of mode change for imprecise computation on multi-core platforms 17

Schedulability analysis of mode change for imprecise computa...

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2017 International conference on Research in Adaptive and Convergent systems, RACS 2017

作者： Shih, Chi-Sheng Yang, Chang-Min Graduate Institute of Networking and Multimedia Department of Computer Science and Info. Eng. National Taiwan University Taipei Taiwan

ISBN: (纸本)9781450350273

Imprecise computation can enhance the responsiveness of computing systems but is rarely applied to embedded real-time systems due to its dynamic computation requirements. With the increasing needs of using image processing for multi-mode safety critical systems, it becomes desired on applying imprecise computation on such systems. In this paper, we extended the traditional schedulability analysis mechanisms on mode change to preemptive multi-core systems for imprecise computation so as to assure that there is no deadline miss between mode changes. The proposed method computes the mode change offset to delay the new mode up to a limit and assure that there is no deadline miss. To evaluate the schedulability of the proposed algorithms, we compare our approach with other works by simulation. The result shows that our analysis can increase schedulability by 15% to 30%, compared to the approach proposed by Lee and Shin in 2013. Moreover, the proposed approach increases the number of completed tasks during mode change up to 40%. © 2017 Association for Computing Machinery.

关键词： image processing

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Managing Diseases Thru' Asclepios: An Agile Information Exploitation Framework

Managing Diseases Thru' Asclepios: An Agile Information Expl...

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IST-Africa Week conference (IST-Africa)

作者： Narasimhan, V. Lakshmi Univ Botswana Gaborone Botswana

ISBN: (纸本)9781538638378

This paper describes the development of an open-source information system, called Asclepios, which manages a plethora of information on communicable diseases in an agile manner. Asclepios exploits information from multiple databases from both open sources (Third Party) and Second party sources. A variety of tools are available in Asclepios to perform extensive processing of numeric and texts (along with some image and video processing) so that trend information can be gleaned on various communicable diseases. The Asclepios architecture draws together a confluence of technologies and industrial standards such as: cloud computing, metadata, ontology generation and management, artificial intelligence, pattern recognition, decision support system, data mining and systems engineering. Because of the use of Component Based Software Engineering (CBSE) methodology for its design, the architecture is scalable, its components replaceable dynamically and configured for the requirements of a given application. The underlying architecture of Asclepios is therefore horizontal, but it has an ability to support several verticals as epidemiology, pharmacology and other fields easily. The application of Asclepios is wide ranging - from military to Government through to medical and tourism and pharmaceuticals. Further, Asclepios-like applications are very much needed in most Third world countries, including all countries in Africa, as it can significantly enhance the health, safety and well-being of people.

关键词： Agile information exploitation Communicable diseases Shallow text processing Cloud computing Metadata generation Ontology management Pattern recognition algorithms

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