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检索条件"任意字段=3rd International Conference on Computer Vision and Image Processing, CVIP 2018"

共 1642 条记录，以下是1551-1560 订阅

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Human Skin Darkness Comparison Using Digital image Analysis

Human Skin Darkness Comparison Using Digital Image Analysis

引用

2018 3rd international conference on Communication,image and Signal processing（CCISP 2018）

作者： D Pour Yousefian Barfeh M C Navarro Department of Computer Science Adamson University

People generally wish to have a lighter or a darker skin. Based on this wish, they regularly compare their skins regarding darkness while there is no simple and accessible system to perform that. This research proposes an algorithm and implements the algorithm in a simple and accessible computerized system that is capable to compare skins of two persons regarding darkness. The system uses digital image processing that accepts an image containing forearms of two persons who are under comparison, then displays some message that expresses the darker skin and the lighter skin. The system uses different techniques such as greyscaling through average method, partitioning and sampling. The system was implemented on an ordinary PC having Linux Ubuntu as operating system, imageLab as library, and C++ as programming language. The results regarding accuracy are presented in different tables. Based on the results, the system has minimum accuracy of 98%.

关键词： image Human Skin Darkness Comparison Using Digital image Analysis

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Face Detection and Classification using Convolutional Neural Network with Channel Attention Module

Face Detection and Classification using Convolutional Neural...

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Mobile Networks and Wireless Communications (ICMNWC), IEEE international conference on

作者： Zainab abed Almoussawi K Sudheer Kumar T. Veena Myasar Mundher Adnan Muhammed Basim Jabar College of Islamic Science Ahl Al Bayt University karbala Iraq Zainb School of Computer Science & Artificial Intelligence SR University Warangal Telangana India Department of Information Technology S.A. Engineering College Chennai India The Islamic University Najaf Iraq National University of Science and Technology Dhi Qar Iraq

Automatic face detection is one of the most challenging in computer vision, FER is a wide range of application in human- computer interaction, behavior, and human expression. However, most of these related researches use general image classification network, which lead inadaptability while applying to face detection. This paper proposed a deep learning using Convolution Neural Network (CNN) with Channel Attention Module. The FER 2013 dataset is utilized in this research for effective classification of face detection. The Data Augmentation is used in this experiment for data pre-processing and feature extraction using high feature generation pyramid (HFGP) and low feature generation pyramid (LFGP). Face detector using Single-Short multi biox detector (SSD) and ResNet 10 based face detection. Then, face detector are given imput to channel attention module classifer which utlized Deep Learning (DL) for effective classification. The obtained result show that the proosed DL using CNN model achieves better accuracy of 99.90% on FER 2013 dataset which ensure accurate classification compared to other existing methods like Engagement Index, Deep Neural Net and Zoning based model.

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Research on Occlusion Relationship Recognition Based on Distance Measurement of Moving Objects in Video 19

Research on Occlusion Relationship Recognition Based on Dist...

引用

Proceedings of the 3rd international conference on Video and image processing

作者： Yandong Li Zhaogong Zhang Zongchao Huang School of Computer Science and Technology Heilongjiang University China

ISBN: (纸本)9781450376822

Aiming at the problem of moving objects occluded in the field of automatic driving, in this paper, we propose a framework for occlusion relationship recognition based on distance measurement of the moving objects in video. The framework performs moving objects detection by YOLOv3 and occlusion recognition of moving objects by the information entropy. When the occlusion occurs, the framework will obtain the distance between the moving objects and the camera by binocular stereo vision distance measurement. Finally, the framework completes occlusion relationship recognition using a principle derived from this paper. The experimental results show that distance measurement of moving objects in video is effective and feasible for occlusion relationship recognition, which can provide some help for visual technology in the field of automatic driving.

关键词： Object detection Binocular stereo vision Occlusion relationship recognition

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Automated Denoising of Diabetic Retinopathy images for Enhanced Medical Diagnosis

Automated Denoising of Diabetic Retinopathy Images for Enhan...

引用

Applied Artificial Intelligence and Computing (ICAAIC), international conference on

作者： G.V. Suresh Gokavarapu Pavani Naga Pranathi Sri Krishna Sai Angidi Tumma Sai Dheeraj Goda Naga Venkata Snehitha Department of Computer Science and Engineering Lakireddy Bali Reddy College of Engineering(Autonomous) Mylavaram India

ISBN: (数字)9798350375190

ISBN: (纸本)9798350375206

Globally, diabetic retinopathy (DR) continues to be a major cause of vision impairment. Early diagnosis and detection of DR are essential to preventing blindness and vision loss. But the traditional manual method of screening retinal pictures takes a lot of time and is prone to human mistake. Using image processing to apply automated denoising techniques can increase image quality, make DR lesions more visible, and help with correct diagnosis. In order to improve the quality of images of diabetic retinopathy, this study investigates the ability of four image denoising filters: guided image filtering, Gaussian-bilateral filtering, Gabor filtering, and Haar Wavelet filtering. AGAR300 (IEEE DataPort), Diabetic Retinopathy Detection, Stare, Indian Diabetic Retinopathy image Dataset, and APTOS 2019 Blindness Detection are the five datasets used to evaluate the efficacy of these filters. The findings demonstrate that noise in DR images may be efficiently reduced by all four filters. The one that shows the biggest overall improvement in lesion visibility and image quality among them is guided image filtering.

关键词： image quality Diabetic retinopathy Noise reduction Visual impairment Blindness Feature extraction Retina

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Determining Lead-Lag Structure between Sentiment Index and Stock Price Returns 2019

Determining Lead-Lag Structure between Sentiment Index and S...

引用

Proceedings of the 3rd international conference on vision, image and Signal processing

作者： Alex Momotov Xianghua Xie Department of Computer Science Swansea University UK

ISBN: (纸本)9781450376259

This research contrasts and compares the state-of-the-art techniques of the two approaches within the domain of news sentiment analysis, as well as, investigates a novel document encoding representation of the 'TF-IDF momentum matrix'. The presented lexicon-based methodology is centred around Loughran & McDonald financial sentiment word lists and reaches 86.4% explained stock momentum variance, whereas the classification approach follows a thematic analysis pipeline implementing Latent Dirichlet Allocation and achieves that of 94.8%. As an additional element of model evaluation, the research implements Thermal Optimal Path method which relies on a dynamic programming approach for performance optimisation.

关键词： Lexicon Lda Stock Price Sentiment Analysis

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Using deep convolutional neural networks with adaptive activation functions for medical CT brain image Classification

Using deep convolutional neural networks with adaptive activ...

引用

Iranian conference of Biomedical Engineering (ICBME)

作者： Roxana Zahedinasab Hadis Mohseni Computer Engineering Department Shahid Bahonar University of Kerman Kerman Iran

ISBN: (纸本)9781538679531;9781538679524

Recently, imaging has become an essential component in many fields of medical research. Analysis of the diverse medical image types requires sophisticated visualization and processing tools. Deep neural networks have introduced themselves as one of the most important branches of machine learning and have been successfully used in many fields of pattern recognition and medical imaging applications. Among the different networks, convolutional neural networks which are biologically inspired variants of multilayer perceptions are widely used in the medical imaging field. In these networks, activation function plays a significant role especially when the data come in different scales. There is a hope to improve the performance of these networks by using adaptive activation functions which adapts their parameters to the input data. In this paper, we have used a modified version of a successful convolutional neural network tuned for medical image classification and investigated the effect of applying three types of adaptive activation functions on that. These activation functions combine basic activation functions in linear (mixed) and nonlinear (gated and hierarchical) ways. The effectiveness of using these adaptive functions is shown on a CT brain images dataset (as a complex medical dataset). The experiments show that the classification accuracy of the proposed network with adaptive activation functions is higher compared to the ones using basic activation functions.

关键词： Computed tomography Convolutional neural networks Biological neural networks Neurons Medical diagnostic imaging

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Software functionalities and requirements for manufacturing systems integration 90

Software functionalities and requirements for manufacturing ...

引用

Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 1

作者： Ching-Yi Wang Dongwoo Lee Computer and Information Science Department New Jersey Institute of Technology Newark NJ

ISBN: (纸本)9780897913720

The meaning of the integration in manufacturing environments is that all component systems work together to meet the company business objectives rather than simply work together. Each component should behave intelligently and actively cooperate with other systems. The issues of integration of a manufacturing system are investigated and applied to vision and image processing system. To achieve the integration, the integrated system is implemented as a collection of objects which are classified into active objects and passive objects. An initial framework for the prototype implementation for an integrated manufacturing system is presented.

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Empirical Analysis of Traffic Sign Recognition using ResNet Architectures

Empirical Analysis of Traffic Sign Recognition using ResNet ...

引用

Advance Computing and Innovative Technologies in Engineering (ICACITE), international conference on

作者： Arunima Jaiswal Deepali Nitin Sachdeva Department of Computer Science and Engineering Indira Gandhi Delhi Technical University for Women India IT Department Galgotias College

Traffic sign recognition is an important task in the field of computer vision and is often used in various applications such as autonomous vehicles, intelligent transportation systems, and road safety systems. Identifying and categorizing the many traffic signs that are present in the environment, such as speed limits, stop signs, and pedestrian crossings, among others, is the goal of traffic sign identification. In this study, we use all iterations of the well-known deep neural network architecture such as Residual Neural Network (ResNet) to conduct an empirical analysis of the recognition of traffic signs. Using the recognition benchmark dataset of German Traffic Signs (GTSRB), which contains 43 different classes of traffic signs, we assess the performance of different ResNet architectures such as ResNet50, ResNet50V2, ResNet101, ResNet101V2, ResNet152 and ResNet152V2. We evaluate all these ResNet architecture performances based on their accuracy, precision, recall, and F1 score. According to the outcomes of our experiments, ResNet50V2 achieves the maximum accuracy of 99.78%, while ResNet152 achieves the lowest accuracy of 99.49%. We also noted that the accuracy of the ResNet50V2 model grows along with the architecture’s depth. To enhance the performance of these DL architectures, image preprocessing techniques such as resizing, zero-centring and normalization is applied to the traffic sign images. The reshaped matrix of the pre-processed images is then fed into the ResNet models according to their architectures. The results of this study demonstrate that the power of different ResNet architectures with image pre-processing, reshaping the matrix, and training time can significantly improve the performance of traffic sign recognition.

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A Survey of Fingertip Character Identification in Open-Air Using image processing and HCI

A Survey of Fingertip Character Identification in Open-Air U...

引用

international conference for Convergence of Technology (I2CT)

作者： Deepti A. Barhate Krunal P. Rane Computer Department MPSTME Shirpur India Electronics and Telecommunication Institute of Technology and Research center Nashik India

Finger spelling recognition using finger motion in blaring area is quiet challenging as communicator are far away from each other they cannot communicate properly as well as this system is also be useful in character recognition on screen or on mobile displays which may help older people, children and computer illiterate people by just making spelling in air using their fingers they can see the word on screen or communicate with each other in blaring area. This system not only just eliminate the barrier of the communication in noisy places but also improve the human computer interaction. this paper is Review on above mentioned system. A 3D camera is used for detecting finger motion and outlines are recognized with one of the characters and numbers in air. Proposed method trials the color of the fingertip and mines the color using filter which gives best results in blaring area also. We will use red colored tape to finger of user to enhance the process captured by finger motion capturing, as it is easy to capture the red color of path than the color of the moving finger. For identification of character or number we are using OCR technology. In view of a situation where the person wants to write a small text or an e-mail and if typing by keyboard or touch was the only choice, they would need to wait for others for help so this system may be useful for them. The major objective of the proposed system is to deliver an commercial result that can change the achieved finger's motion of alphabets to text in a editor and help as effective means of HCI. The major application of this system will be at traffic control system, airports, enterprises, virtual environment, 3D gaming and so on. This paper presents the study of the methodologies useful for identifying motion in real time application

关键词： Thumb image color analysis Character recognition Videos Gesture recognition Optical character recognition software

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Digital Watermarking Algorithm for 2D Vector Graphics 2019

Digital Watermarking Algorithm for 2D Vector Graphics

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Proceedings of the 3rd international conference on vision, image and Signal processing

作者： Yue Ding Jianrong Wang Xiang Ying School of computer software College of intelligence and computing Tianjin University Tianjin China School of Computer Science and Technology College of intelligence and computing Tianjin University Tianjin China

ISBN: (纸本)9781450376259

At present, digital watermark technology has been relatively mature in the security protection of images, video, audio and other fields, and has achieved many successful applications. In contrast, there are relatively few watermarking methods for vector graphics copyright protection. We propose a digital watermarking algorithm for the vector graphics drawn by the spline. Firstly, we grab the color values of vector graphics and construct a color matrix. Then DWT decomposition and Slant transformation are performed on the color matrix. Finally, the watermark image is embedded in the low frequency component of the color matrix. Experimental results show that not only the watermark information is successfully hidden to the vector graphics, but also the algorithm can effectively resist object modification attacks.

关键词： Spline Curve Digital Watermarking Copyright Protection

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