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

共 15616 条记录，以下是4531-4540 订阅

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Large Scale image Dataset Construction Using Distributed Crawling with Hadoop YARN 10

Large Scale Image Dataset Construction Using Distributed Cra...

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Joint 10th International conference on Soft Computing and Intelligent systems (SCIS) / 19th International Symposium on Advanced Intelligent systems (ISIS)

作者： Ali, Asmat Ali, Rahman Khattak, Asad Masood Aslam, Muhammad Saqlain Univ Peshawar Dept Comp Sci Peshawar Pakistan Univ Peshawar Quaid E Azam Coll Commerce Peshawar Pakistan Zayed Univ Coll Technol Innovat Dubai U Arab Emirates Natl Cent Univ Dept Comp Sci & IT Taoyuan Taiwan

ISBN: (纸本)9781538626337

with the rapid advancement in the internet, we are now living in the era of big data. The image data over the web has the potential to assist in the development of sophisticated and robust models and algorithms to interact with images and multimedia data. images Data sets are widely used in image processing tasks and analyses. They are in use in various fields including Artificial Intelligence, Data extraction and collection, Computer vision, Research studies and education. In this research work, we are going to propose a system that crawls the web in a systematic manner using Hadoop MapReduce technique to collect images from millions of web pages on the web. With Celebrity images just a use case, we would be able to search for and retrieve any image tagged with some specific terms. The system uses some simple techniques to reduce noisy images like thumbnails and icons. The proposed system is based on Apache Hadoop and Apache Nutch, an open source web crawler. A customized crawl is run through Apache Nutch in a Hadoop Cluster that searches images for one or more categories on the web and retrieves their links. Next, HIPI, Hadoop image processing Interface is used to download the images and create datasets for an individual category or a dataset of multiple categories.

关键词： Hadoop YARN Apache Nutch Web Crawling Web Scrapping Distributed Computing image Search

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KES International conferences on Innovation in Medicine and Healthcare, KES-InMed 2019 and Intelligent Interactive Multimedia systems and Services, KES-IIMSS 2019

KES International conferences on Innovation in Medicine and ...

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KES International conferences on Innovation in Medicine and Healthcare, KES-InMed 2019 and Intelligent Interactive Multimedia systems and Services, KES-IIMSS 2019

ISBN: (纸本)9789811385650

The proceedings contain 55 papers. The special focus in this conference is on Innovation in Medicine and Healthcare. The topics include: Logistic Map and Contourlet-Based Robust Zero Watermark for Medical images;a Sensor Platform for Non-invasive Remote Monitoring of Older Adults in Real Time;Deep Learning for Detecting Breast Cancer Metastases on WSI;advanced image processing algorithms for Breast Cancer Decision Support and Information Management System;FDCT and Perceptual Hash-Based Watermarking Algorithm for Medical images;Comparison of CNN Models with Different Plane images and Their Combinations for Classification of Alzheimer’s Disease Using PET images;multimodal Behavioral Dataset of Depressive Symptoms in Chinese College Students–Preliminary Study;contour Lines to Assist Position Recognition of Slices in Transparent Stereoscopic visualization of Medical Volume Data;fused visualization and Feature Highlighting to Assist Depth Recognition in Transparent Stereoscopic visualization;archiMate Business Model Patterns to e-Healthcare;A NIRS Study of Different Colour Effects on Short Memory Tasks Between Young and Elderly Subjects;biomechanical Analysis of Human Gait with Inertial Sensors Using Neural Networks;data Mining Electronic Health Records to Support Evidence-Based Clinical Decisions;Formalization of the Agent-Based Model for the Detection of Behavior Patterns in Older Adults Who Start Using ICT;mHealth Application for Fast Attention to People with Cerebrovascular and Cardiovascular Urgencies;ioT in Medical Context: Applications, Diagnostics, and Health Care;contributions of Machine Learning in the Health Area as Support in the Diagnosis and Care of Chronic Diseases;big Data and Predictive Health Analysis;automatic Quantification of Breast Arterial Calcification on Mammographic images.

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Color image Noise Removal Algorithm Implementation using Blackfin Dual Core Microcontroller

Color Image Noise Removal Algorithm Implementation using Bla...

引用

International conference on Telecommunications in Modern Satellite, Cable and Broadcasting Service (TELSIKS)

作者： Sorin Zoican Roxana Zoican Dan Galatchi Faculty of Electronics Telecommunications and Information Technology Politehnica University of Bucharest Bucharest Romania

ISBN: (数字)9781728108780

ISBN: (纸本)9781728108797

This paper presents an implementation of noise removal from a color image using bilateral filter and wavelet transform based on dual core Blackfin microcontrollers. The tasks organization between the two cores and calculus optimizations are illustrated in a framework for image processing. The obtained results show that the proposed framework can be successfully used to achieve a real time implementation for noise removal in video clips for medium size images.

关键词： Filtering algorithms image color analysis Task analysis Streaming media Microcontrollers Transforms

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F-transform-Based Optimization for image Restoration (Inpainting)

F-transform-Based Optimization for Image Restoration (Inpain...

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IEEE International conference on Fuzzy systems (FUZZ-IEEE)

作者： Perfilieva, I. Univ Ostrava Inst Res & Applicat Fuzzy Modeling NSC IT4Innovat 30 Dubna 22 Ostrava 70103 1 Czech Republic

ISBN: (纸本)9781509060207

In image processing, the inpainting (image restoration) problem is often considered with respect to the interpolation. We involve into the solution of this problem the F-transform-based nonlocal operators that define a new type offunctionals, extending the ability ofclassical PDE-based algorithms in handling textures and repetitive structures. We showed that in the particular space with a fuzzy partition, the nonlocal Laplacian and partial derivatives can be represented by the F-0- and F-1-transforms. for the inpainting problem specified by relatively large damaged areas, we propose a new total variation model with the F-transform-based nonlocal operators. We show that the proposed model together with the corresponding algorithm increase the quality of a (usually considered) patch-based searching algorithm.

关键词： F-transform fuzzy partition image restoration total variation ROF model

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Fast training and real-time classification algorithm based on Principal Component Analysis and F-transform 10

Fast training and real-time classification algorithm based o...

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Joint 10th International conference on Soft Computing and Intelligent systems (SCIS) / 19th International Symposium on Advanced Intelligent systems (ISIS)

作者： Hurtik, Petr Perfilieva, Irina Univ Ostrava CEIT4I IRAFM Ostrava Czech Republic

ISBN: (纸本)9781538626337

While machine learning algorithms become more and more accurate in image processing tasks, their computation complexity becomes less important because they can be run on more and more powerful hardware. In this work, we are considering the computation complexity of a machine learning algorithm training/classification phase as the major criterion. The main aim is given to the Principal Component Analysis algorithm, which is examined, its drawbacks are point-out and suppressed by the proposed combination with the F-transform technique. We show that the training phase of such a combination is very fast, which is caused by the fact that both PCA and F-transform algorithms reduce dimensionality. In the designed benchmark, we show that the success rate of the fast hybrid algorithm is the same as the original PCA, due to F-transform ability to capture spatial information and reduction of noise/distortion in an image. Finally, we demonstrate that PCA+FT is faster and can achieve a higher success rate than a standard Convolution Neural Network and nevertheless, it is slightly less accurate as a Capsule Neural Network for the chosen dataset, its training phase is 100000 x faster and classification time is faster 9x.

关键词： Principal Component Analysis PCA F-transform image classification algorithm complexity

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Annotated 360-Degree image and video Databases: A Comprehensive Survey

Annotated 360-Degree Image and Video Databases: A Comprehens...

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International conference on Signal processing and Communication systems, ICSPCS

作者： Majed Elwardy Hans-Jürgen Zepernick Veronica Sundstedt Blekinge Institute of Technology Karlskrona Sweden

ISBN: (数字)9781728121949

ISBN: (纸本)9781728121956

The advances in 5G mobile networks are expected to enable immersive interconnected mobile multimedia systems. As humans are the final judges of the quality of immersive multimedia, it is essential to engage a suitable ground truth in the design of such systems. Databases annotated with results from subjective tests constitute such ground truth given as opinion scores, head movements, eye tracking data, psychophysiological data, and other data related to the viewers' behavior. On this basis, perception-based quality assessment of algorithms, systems, and services can be performed, and objective perceptual quality models can be developed. In this paper, a comprehensive survey of publicly available annotated 360-degree image and video databases is provided. The survey may guide the selection of ground truth on 360-degree images and videos to support quality assessment and modeling research. Further, the survey reveals the need for establishing new annotated databases that address the full range of subjective aspects of immersive multimedia.

关键词： Streaming media Head Quality assessment visualization Multimedia databases Observers

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Poster Abstract: An Automated Real-time and Affordable Airborne Pollen Sensing System

Poster Abstract: An Automated Real-time and Affordable Airbo...

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International Symposium on Information processing in Sensor Networks (IPSN)

作者： Nam Cao Olga Saukh Lothar Thiele Institute of Technical Informatics Graz University of Technology ETH Zurich Computer Engineering and Networks Lab

ISBN: (纸本)9781728107271

In this paper, we present the design of our prototype of an automated real-time and affordable pollen sensing system. The design consists of three main subsystems: (1) a trap with automatic filtering, (2) a particle concentration system, and (3) a digital microscope with autofocus. The prototype shows effective particle gathering, filtering and concentration in a tiny sized area. As a result, we reduce particle loss and improve image quality taken by the optical system when searching and autofocusing on pollen grains. Our first prototype collects raw time-stamped data and transmits these to the backend server where we plan to run the detection and classification algorithms to extract accurate pollen counts from microscopic images. The key advantage of processing images at the backend is that we let the experts undertake corrective actions and help the system learn to detect and classify pollen using state-of-the-art interactive imitation learning algorithms. The final model can then run locally on embedded hardware.

关键词： Microscopy Prototypes Cyclones Sensors Real-time systems Filtering image resolution

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Objects Detection and Recognition in videos for Sequence Learning

Objects Detection and Recognition in Videos for Sequence Lea...

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IEEE International conference on Cognitive Informatics

作者： Yingxu Wang Tony Cai Omar Zatarain International Institute of Cognitive Informatics and Cognitive Computing (ICIC) Schulich School of Engineering and Hotchkiss Brain Institute University of Calgary 2500 University Drive NW Calgary Alberta Canada

ISBN: (数字)9781728114194

ISBN: (纸本)9781728104966

A key challenge to sequence learning for video comprehension is objects detection and localization in dynamic and real-time environment. This paper presents two methodological approaches to autonomous and generic object detection and localization in video sequences. algorithms for both facial and non-facial object localization, as well as their integration, are developed. A set of experiments and case studies for practical video image processing is demonstrated for sequence learning. This work paves a way to sequence learning towards enhanced computer and robot vision technologies in applications of self-driving cars and real-time facial recognition.

关键词： Object detection videos image edge detection Clustering algorithms Real-time systems Heuristic algorithms visualization

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A Study on the processing and Reinforcement of Message Digest Through Two-Dimensional Array Masking 32

A Study on the Processing and Reinforcement of Message Diges...

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32nd International conference on Information Networking (ICOIN)

作者： Park, Sun-young Kim, Keecheon Konkuk Univ Dept IT Convergence Informat Secur Seoul South Korea Konkuk Univ Dept Comp Sci & Engn Seoul South Korea

ISBN: (纸本)9781538622902

Hash algorithms have been widely used for cryptography. It has been impossible to decrypt the ciphertexts generated through hash algorithms, as an operation that damages the original text is performed. The vulnerability of SHA1 (an old hash algorithm) has been revealed, and there has been a great deal of data available for dictionary attacks. Although the industry has been gradually refraining from using SHA1, it remains in use in some existing systems for various reasons. In particular, when problems resulting from medical service interruption or mass update are directly related to a person's life, updating the encryption algorithm can be a burden. In this study, we aim to increase the complexity of ciphertexts by postprocessing hash ciphertext by masking message digest to a two-dimensional array constructed using an image processing technique. This will allow the use of hash ciphertexts with increased complexity in some medical devices that are forced to use old hash algorithms for various reasons.

关键词： Hash Algorithm image processing rainbow table message Digest two-dimensional array

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image Classification Based on BP Neural Network and Sine Cosine Algorithm

Image Classification Based on BP Neural Network and Sine Cos...

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IEEE International conference on Intelligent Data Acquisition and Advanced Computing systems

作者： Haoqiu Song Zhiwei Ye Chunzhi Wang Lingyu Yan School of Computer Science Hubei University of Technology China Key Laboratory of Intelligent Computing and Information Processing Fujian Province University China

image classification is one of the most important tasks in image analysis and computer vision. BP neural network is a successful classifier for the task. However, with regard to the low study efficiency and the slow convergence speed in BP algorithm, some optimization algorithms have been proposed for achieving better results. Among all these methods, BP neural network improved by particle swarm optimization (PSO) and genetic algorithm (GA) may be the most successful and classical ones. Nevertheless, both GA and PSO are easy to fall into the local optimal solution, which has a great impact on the precision of classification. As a result, a novel optimization algorithm called sine cosine algorithm (SCA) is presented to improve the classification performance. The experimental results manifest that the proposed method has good performances, and the classification accuracy is better than BP neural network optimized by GA, PSO or other algorithms.

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