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检索条件"任意字段=2nd International Conference on Computer Vision and Image Processing, CVIP 2017"

共 1830 条记录，以下是1201-1210 订阅

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Classification of Low Resolution Astronomical images using Convolutional Neural Networks 2

Classification of Low Resolution Astronomical Images using C...

引用

2nd IEEE international conference on Recent Trends in Electronics, Information and Communication Technology (RTEICT)

作者： Patil, Jyoti S. Pawase, Ravindra S. Dandawate, Y. H. VIIT Dept Elect & Telecommun Engn Pune Maharashtra India VIIT Dept Engn & Appl Sci Pune Maharashtra India

ISBN: (纸本)9781509037049

Currently deep machine learningtechniques are widely adopted by computer vision and signal processing communities. Deep learning, in particular, the Convolutional Neural Networks (CNN), are the most impressive classifiers widely used for image classification in recent years. CNN model allows the machine to learn automatically about the complex image features from its representation, minimizing the need of human experts in feature extraction. Such a hierarchical representation learning of the images makes CNN a more promising model for classification of different kinds of images as compared to the traditional machine learning models. In this paper, one such successful implementation of CNN is performed for classifying low resolution radio astronomical images containing objects like 'Radio Halos and Relics', and several other ` Point Radio Sources'. For such images, low resolution makes feature extraction a difficult task. Hence, a CNN based classification model proved more efficient in this casegiving a classification accuracy of 88%.

关键词： image classification machine learning convolutional neural networks deep learning

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Physiological Modeling of Retinal Layers for Detecting the Level of Perception of People with Strabismus 2nd

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2nd international conference on Intelligent Computing and Applications (ICICA)

作者： Rajalakshmi, T. Prince, Shanthi SRM Univ Dept Biomed Engn Kattankulathur 603203 India SRM Univ Dept ECE Kattankulathur 603203 India

ISBN: (纸本)9789811016455;9789811016448

In the process of visual recognition, the human visual system (HVS) model provides a pathway on evaluating the image quality and there by detecting the performance of the human observer. Squint eye is the term associated with the misalignment in projection of the eye and hence provides binocular vision. Mathematical modeling of retina plays a vital role to produce better visual perception. The main aim of this work is to develop an HVS (human visual system) model for detecting the perceptual level of people with strabismus (squint). People with normal vision is capable of perceiving as one single image when the image falls on the retina. The situation is not the same in case of people with strabismus. One of the main symptoms of strabismus people is double vision, which is the simultaneous perception of two images of a single object. This paper focuses on the mathematical modeling of retinal layers namely photoreceptor, outer-plexiform and inner-plexiform layers and to provide an insight knowledge on the occurrence of double vision in the case of people with strabismus (medical term used for squint eye). It is proved through the proposed model that the energy level of normal vision person is higher than people with strabismus and the intensity level is approximately the same after processing through the photoreceptor layer.

关键词： Human visual system (HVS) Strabismus Binocular vision Compression Perception

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PCB Defect Detection USING OPENCV with image Subtraction Method 2

PCB Defect Detection USING OPENCV with Image Subtraction Met...

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2nd international conference on Information Management and Technology (ICIMTech)

作者： Raihan, Fa'Iq Ce, Win Bina Nusantara Univ Sch Informat Syst Dept Informat Syst Jakarta 11480 Indonesia

ISBN: (纸本)9781538629307

In the PCB manufacturing industry, one of the most important aspect of the production is quality checking. PCB boards goes through lots of production process from panel cutting to laminating and one single defect in a board will make the entire board become obsolete. With the rise of electronic appliances demand every day, the demand for higher quality components is rising. With the high price tag of commercial AOI, lots of manufacturers are not able to do an automated inspection. This is where computer vision can provide an alternative for commercial AOI to assist small scale manufacturers to do an automated inspection. image Subtraction and Blob detection enable users to easily find numerous visual defects in PCBs especially with a complex method. By dissecting pictures and pointing out the differences on the output image, PCBs can be inspected quickly to find out the defective parts. And thus, this thesis will focus on the basis that a basic image subtraction will be enough to assist Manufacturers in Quality Inspections.

关键词： AOI OpenCV computer vision PCB image Subtraction

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Multi-Threading image processing in Single-core and Multi-core CPU using R Language 2

Multi-Threading Image Processing in Single-core and Multi-co...

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2nd IEEE international conference on Electrical, computer and Communication Technologies (IEEE ICECCT)

作者： Ramalakshmi, E. Kompala, Neeharika Chaitanya Bharathi Inst Technol Dept Informat Technol Hyderabad Andhra Prades India

ISBN: (纸本)9781509032396

R language executes its program on a one core CPU by default, using image processing. R language requires gigantic amount of calculations which are all processed by one core itself. When there is a need to use multiple core present in our platform, special packages in R language are used and executed. image processing requires a large number of resources and processing all running simultaneously, and all the calculations are majorly done with the help of matrix pixels. In order to see how single-core and Multi-core systems affect the efficiency of image processing algorithms we execute codes on multiple platforms with varying number of codes along with varying sizes of the image. Also we use the concept of threading, and performing the same function both as a single thread process and a Multi thread process to check its efficiency. An increase on the performance as a whole can be observed when we change the number of codes, size of images and also as we choose to implement thread concepts.

关键词： R language image processing Single-core Multicore Multi-Threading

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A Fast SISR Technique Founded on Synthesize High-Band Frequency and An Adaptive Hampel Stochastic Function 2

A Fast SISR Technique Founded on Synthesize High-Band Freque...

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2nd international conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)

作者： Thakulsukanant, Kornkamol Patanavijit, Vorapoj Assumption Univ Bangkok Thailand

ISBN: (纸本)9781509066643

Theoretically, the conventional image enlarging technique is a mathematical method for building a superior enriched resolution image, which is normally insisted for modern computer vision and image processing application by utilizing only one poor resolution image, which is normally captured from any commercial embedded camera systems. Due to the fast computation, the Single-image Super-Resolution (SISR) is one of the well-known Super Resolution-Reconstruction (SRR) techniques and the SISR is desired for applying on only one poor resolution image. Therefore, this article aims to present the image enlarged technique founded on SISR algorithm utilizing Hampel stochastic function and high-band frequency synthesizing. Unfortunately, the efficacy of the SISR technique is relied upon three parameters (b, h, k) and it is difficult task for estimating these suitable values of these three parameters for reconstructing the superior enriched resolution image with the optimum Peak Signal-to-Noise Ratio (PSNR). In consideration of deciphering to this problem, the Hampel stochastic function, which is relied upon wholly one parameter (T), instead of three parameters like the conventional function, is comprised into SISR technique. By studying on 14 classic images, which are corrupted by different noise models, in the statically exploratory section, the efficacy of the fast SISR technique closely equal to the conventional SISR technique but the parameter adjustment process of the proposed fast SISR technique (with one parameter) is more simple and fasert than the conventional SISR technique (with three parameters). Because of fast computation in the parameter adjustment process, the proposed fast SISR technique is more suitable for real implementation.

关键词： Hampel Stocastic Function SRR (Super Resolution-Reconstruction) image Enlarged Technique

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Design and implementation of fuzzy image enhancement system in police application

Design and implementation of fuzzy image enhancement system ...

引用

2018 2nd international conference on Electronic Information Technology and computer Engineering (EITCE 2018)

作者： Cheng LIU Fan-liang BU People's Public Security University of China School of Information Technology and Network Security

A set of image processing system based on fuzzy image enhancement algorithm is designed and implemented in the light of the actual needs of image material evidence extraction in the criminal investigation process of public security department, which is combined with the computer technology such as C++ language and graphic development tools. The system can enhance the processing efficiency by continuously selecting different algorithms for input images. The same type of fuzzy image can be processed by various algorithms and the ideal image can be obtained by comparing the image evaluation indexes, and the optimal selection of image quality and algorithm is realized.

关键词： Retinex Design and implementation of fuzzy image enhancement system in police application image

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Gate Level Information Flow analysis for multi-valued logic system 2

Gate Level Information Flow analysis for multi-valued logic ...

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2nd international conference on image, vision and Computing, ICIVC 2017

作者： Tai, Yu Hu, Wei Guo, Lantian Mao, Baolei Mu, Dejun School of Automation Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9781509062379

As the scale of integrated circuits continuously increasing, guaranteeing intensity of testing and coverage rate of verification in the design phase absolutely is becoming severe challenges. As a solution, Gate Level Information Flow Tracking (GLIFT) method is able to precisely measure all the logical information flows in the underlying hardware to prevent information leakage resulting from these harmful flows of information. However, preliminary research work for GLIFT mainly focused on the basic theories as well as the generation algorithms, which only can track logic formalization under the Boolean logic system. These approaches ignored that digital circuits are typically described by multi-valued logic during hardware design and verification. To address that issue, we present to expand the GLIFT method for multi-valued logic system. In this paper, the label propagation rule set is respectively derived for four-valued and nine-valued logic systems by extending the label propagation set for Boolean logic. Moreover, in order to support the characteristics of multi-valued logic in label propagation, the formal descriptions of GLIFT logic for primitive gates are improved in computing hardware as well. The experimental results demonstrate that the extended method is consistent with the label propagation rule of the multi-valued logic system. © 2017 IEEE.

关键词： computer circuits

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2017 2nd Asia-Pacific conference on Intelligent Robot Systems, ACIRS 2017

2017 2nd Asia-Pacific Conference on Intelligent Robot System...

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2nd Asia-Pacific conference on Intelligent Robot Systems, ACIRS 2017

ISBN: (纸本)9781509067923

The proceedings contain 68 papers. The topics discussed include: a multimodal gesture-based virtual interactive piano system using computer vision and a motion controller;recognition and location of solar panels based on machine vision;an implementation framework for fast image processing;a novel image retrieval model based on semantic information and probability rough set analysis method;study on the movable detection method about inland vessels ultra-draft violations;tongue shape classification integrating image preprocessing and convolution neural network;online image Jacobian identification using optimal adaptive robust Kalman filter for uncalibrated visual servoing;vision-based localization in campus with a multi-stage framework;classification based on label semantic characteristic analysis;a method for improving consistency of judgment matrix in the AHP;the fluorescence spectroscopy recognition of the traditional Chinese medicine injection based on the lifting wavelet- BP-fuzzy neural network;researchment of metadata-driven based informatization strategy of parameter' life cycle management;application of time-space complex envelope technique in time-domain near-field acoustic holography;semi-bit frequency compensation differential combining post-correlation processing for GNSS weak signal environment;and design of control system for fixed double propellant unmanned surface vehicle based on Moos-IvP.

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2017 IEEE 2nd international conference on Signal and image processing, ICSIP 2017

2017 IEEE 2nd International Conference on Signal and Image P...

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2nd IEEE international conference on Signal and image processing, ICSIP 2017

ISBN: (纸本)9781538609682

The proceedings contain 97 papers. The topics discussed include: improved k-d tree-segmented block truncation coding for color image compression;an error detection and recovery technique for images compressed with the CCSDS compression algorithm;adaptive compressive-sensing of 3D point clouds;compressed sensing MRI with total variation and frame balanced regularization;medical image fusion based on GPU accelerated nonsubsampled shearlet transform and 2D principal component analysis;a novel approach on classification of infant activity post surgery based on motion vector;automatic localization of optic disc based on deep learning in fundus images;a novel compensation algorithm of aerial image registration;three-dimensional positioning using ALOS/prism triple linear-array satellite images;digital anthropometry for human body measurement on android platform;stacked hidden Markov model for motion intention recognition;image processing algorithm for extracting the phase map from structured lights;supervised 3D graph-based automated epidermal thickness estimation;optimizing cognitive analysis sensitivity of photospheres using cube maps;detecting AMD caused vision scotoma through eye tracking;and learning visual odometry for unmanned aerial vehicles.

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Automatic Data Acquisition-A Major Challenge 2

Automatic Data Acquisition-A Major Challenge

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2nd IEEE international conference on Electrical, computer and Communication Technologies (IEEE ICECCT)

作者： Challa, Nagendra Panini Mehta, R. Vasanth Kumar SCSVMV Univ Dept CSE Kanchipuram Tamil Nadu India

ISBN: (纸本)9781509032396

This paper describes about the active research work undergoing in SCSVMV University with respect to palm leaf manuscripts (PLMs). The challenges are identified from the experience of digitizing and cataloguing those PLMs manually. There is a need to organize these collections with proper metadata format and extracting them automatically. Some elements in metadata are calculated using digital image processing algorithms which help in automatic extraction of metadata. However major challenges are addressed where active research work is going on to give an enhanced solution.

关键词： Palm Leaf Manuscripts Digitizing Cataloguing Metadata Digital image processing Automatic Extraction

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