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

共 1803 条记录，以下是841-850 订阅

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Evolution Analysis of Adaptive Distance-Preserving Level Set for image Segmentation Based on Depth Learning 2

Evolution Analysis of Adaptive Distance-Preserving Level Set...

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2nd international conference on computer Information Science and Application Technology, CISAT 2019

作者： Wang, Jinpeng Li, Jing College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao266590 China

image segmentation technology is the most basic part of computer vision and the basis of all other image processing methods. The quality of image segmentation technology will affect the effect of subsequent processing to a large extent. In the research and application of computer vision, image segmentation is often the first step and plays a very important role in the whole process. Compared with image classification and target detection, Distance-Preserving level set method involves two cross-cutting areas of image recognition and natural language processing, which is very challenging. Handling the information interaction between the machine and the real world is the first step in the study of artificial intelligence. The goal of computer vision research is to make the computer have the ability to perceive and understand image information. In the future, the focus of the work will be on improving the generalization ability of the model so that the model can perform well in a variety of tasks. © 2019 IOP Publishing Ltd.

关键词： image segmentation

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Detection of Overall Fruit Maturity of Local Fruits using Convolutional Neural Networks Through image processing 2019

Detection of Overall Fruit Maturity of Local Fruits using Co...

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2nd international conference on Computing and Big Data (ICCBD)

作者： Ayllon, Mark Anthony Cruz, Melwin James Mendoza, Justin Jason Tomas, Mary Christine Mapua Univ Sch Informat Technol Makati Philippines

ISBN: (纸本)9781450372909

Determining the ripening of a fruit is critical to a farmer, since the fresher the fruit, the better it will be priced and sold. This is also critical to the economy since the ninth (9th) most exported good in the Philippines is fruits. The researchers made use of Convolutional Neural Networks through image processing to determine the fruit maturity of Banana (Cavendish), Mango (Carabao), Calamansi/Calamondin, will classify said fruits into three categories for the fruit maturity: pre-matured, matured, over-matured. Of the sixty fruits used, twenty pieces of which will be used to gather data, starting from their very unripe/pre-matured stage up-to the over-matured stage. This will approximately take one (1) to two (2) weeks if stored in room temperature. The total data gathered would be 3681 pieces for Calamansi (Philippine lime);3270 pieces for Banana (Cavendish);and 5706 pieces for Mango (Carabao). The model is written in Spyder in Anaconda Navigator, which will be applying Tensorflow-GPU and Keras. These will also be coupled with CUDA and CUDDN to process the data and determine the results. Two total experiments will be executed - one for the Red-Green-Blue (RGB) dataset, and one for the greyscale dataset.

关键词： computer vision Convolutional Neural Network Fruit Maturity image processing

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Do GANs Leave Artificial Fingerprints? 2

Do GANs Leave Artificial Fingerprints?

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2nd IEEE international conference on Multimedia Information processing and Retrieval (MIPR)

作者： Marra, Francesco Gragnaniello, Diego Verdoliva, Luisa Poggi, Giovanni Univ Federico II Naples Dept Elect Engn & Informat Technol Naples Italy

ISBN: (纸本)9781728111988

In the last few years, generative adversarial networks (GAN) have shown tremendous potential for a number of applications in computer vision and related fields. With the current pace of progress, it is a sure bet they will soon be able to generate high-quality images and videos, virtually indistinguishable from real ones. Unfortunately, realistic GAN-generated images pose serious threats to security, to begin with a possible flood of fake multimedia, and multimedia forensic countermeasures are in urgent need. In this work, we show that each GAN leaves its specific fingerprint in the images it generates, just like real-world cameras mark acquired images with traces of their photo-response non-uniformity pattern. Source identification experiments with several popular GANs show such fingerprints to represent a precious asset for forensic analyses.

关键词： image forensics GAN image fingerprint

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An Examination of Different vision based Approaches for Road Anomaly Detection 2

An Examination of Different Vision based Approaches for Road...

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2nd international conference of the IEEE-Nigeria-computer-Chapter (NigeriaComputConf)

作者： Bello-Salau, H. Onumanyi, A. J. Salawudeen, A. T. Mu'azu, M. B. Oyinbo, A. M. Ahmadu Bello Univ Dept Comp Engn Zaria Nigeria Fed Univ Technol Minna Dept Telecommun Engn Minna Nigeria

ISBN: (纸本)9781728107134

Recent advances in vehicular technology and sensing devices has led to the proliferation of different approaches for road surface condition monitoring and road anomaly detection. These approaches can be categorized into vision-based and accelerometer-based techniques. These techniques are designed to enable vehicles detect road anomalies and notify drivers of such, thereby reducing the rate of anomalous induced accidents. Also, these approaches can be incorporated into autonomous vehicles towards navigating through road terrains with anomalies such as potholes, speed bumps and rutting. The vision-based techniques have received wide acceptance among academia and industry players alike because of their inherent ability to detect road anomalies in real-time and notify drivers easily. In this regard, this paper presents a mini-survey of various state-of-the-art vision-based techniques proposed in the literature for road surface condition monitoring and anomaly detection. The merits and drawbacks of these techniques are highlighted. Furthermore, open research issues are presented. Our effort forms part of a larger goal aimed at developing robust vision processing approaches for road anomaly detection, as well as benefiting researchers involved in similar pursuits.

关键词： image Potholes Road Speed-Bumps Smartphone and Segmentation

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On-line inspection and sorting system for mechanical parts based on machine vision 2

On-line inspection and sorting system for mechanical parts b...

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2nd international conference on Information Technologies and Electrical Engineering, ICITEE 2019

作者： Jiang, Chunling Wei, Qiang Feng, Baitao School of Physics and Electronic Engineering Taishan University Shandong Tai'an China

ISBN: (纸本)9781450372930

Based on machine vision, this paper uses Matlab to perform image processing and image recognition on the image signals of mechanical parts collected, and transmits the control signals wirelessly through Zigbee to realize on-line detection and sorting of mechanical parts. Taking a complex workpiece with multiple circular holes as an example, the structure and implementation method of the system are introduced. The system has the advantages of low cost, high precision and easy installation. Its non-contact, real-time, flexibility and accuracy can effectively solve the problems of traditional detection methods. © 2019 ACM.

关键词： computer vision

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Extraction of Features from Video Files Using Different image Algebraic Point Operations 19

Extraction of Features from Video Files Using Different Imag...

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2nd international conference on image and Graphics processing (ICIGP) / 5th international conference on Virtual Reality

作者： Dutta, Pranti Nachamai, M. Christ Univ Dept Comp Sci Bengaluru 560029 India Siemens India Bengaluru 560100 India

ISBN: (纸本)9781450360920

In the human-computer interaction (HCI) field, facial feature analysis and extraction are the most decisive stages which can lead to a robust and efficient classification system like facial expression recognition, emotion classification. In this paper, an approach to the problem of automatic facial feature extraction from different videos are presented using several image algebraic operations. These operations deal with pixel intensity values individually through some mathematical theory involved in image analysis and transformations. In this paper, 11 operations (point subtraction, point addition, point multiplication, point division, edge detecting, average neighborhood filtering, image stretching, log operation, exponential operation, inverse filtering, and image thresholding) are implemented and tested on the images (video frames) extracted from three different self-recorded videos named as video1, video2, video3. The videos are in .avi, .mp4 and .wmv format respectively. The work is tested on two types of data: grayscale and RGB (Red, Green, Blue). To assess the efficiency of each operation, three factors are considered: processing time, frames per second (FPS) and sharpness of edges of feature points based on image gradients. The implementation has been done in MATLAB R2017a.

关键词： Feature extraction image algebra Video frame Point operation

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Transfer Learning Approach for Plant Leaf Disease Detection Using CNN with Pre-Trained Feature Extraction Method Mobilnetv2

Transfer Learning Approach for Plant Leaf Disease Detection ...

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international conference on Robotics,Electrical and Signal processing Techniques (ICREST)

作者： Raida Moyazzoma Md. Al Amin Hossain Md. Hasanuzzaman Anuz Abdus Sattar Daffodil International University Dhaka Bangladesh

ISBN: (数字)9781665415767

ISBN: (纸本)9781665415774

Economy of Bangladesh mostly depended on agriculture. As a small country, our population is over the limit. We are also a developing country also. For national GDP growth must be to increase the production. Every year a huge amount of agricultural production losses for the crop disease. As we know most of the farmers in our country are illiterate, have no proper knowledge about the disease, that's why they cannot manually detect the disease. I think if you properly detect the disease at the early stage we can solve the issue. We develop a model that can classify leaf disease. We focus on 5 major production crops in Bangladesh. Using computer vision technique our farmer will get the benefit. We use convolutional neural networks for classifying images. An algorithm cannot properly capture the features of existing data that's why we use a pre-trained feature extraction method that is MobileNetv2. MobileNetv2 is very useful for mobile devices. The research contains the proportions of validation accuracy of 90.38%. This approach resulted in the agriculture sector that will help a farmer to classify disease from harvest. The main goal of our model is to minimize the damage of suffering plants that can help to the growth of production. By solving this issue themselves farmers can also reduce cost. Our goal is that they can cure their crop at the right time. To achieve this goal we tend to think that we should develop a way to detect the leaf disease. We collect several kinds of cucumber leaves. And then any leave can be tasted by our model. By using our model we try to reduce the leaf disease.

关键词： Convolution Computational modeling Production Feature extraction Agriculture Diseases image classification

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A Novel Approach to Glaucoma Screening using computer vision 2

A Novel Approach to Glaucoma Screening using Computer Vision

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2nd international conference on Smart Systems and Inventive Technology, ICSSIT 2019

作者： Chakrabarty, Navoneel Chatterjee, Subhrasankar Computer Science and Engineering Jalpaiguri Government Engineering College Jalpaiguri West Bengal India

ISBN: (纸本)9781728121192

Glaucoma is one of the major and critical eye diseases discovered till date. It is actually a group of diseases that damage the optic nerve and subsequently result in vision loss and blindness. One of the major causes of Glaucoma is the intrinsic distortion of the optic nerve resulting in high fluid pressure on the front portion of the eye. The primary objective of the paper is to classify High Resolution Fundus images of the retina into Glaucomatous and Non-Glaucomatous. In order to achieve that, a DL-ML Hybrid Model has been developed with an initial image processing. The overall methodology followed in this paper has been termed as N-S Model. The HRF (High Resolution Fundus) image Database consisting of 30 images is used for the purpose. The N-S Model was deployed after development and clocked a 100% Validation Accuracy and Sensitivity of 1.0. Such an Intelligent System can accelerate the process of diagnosis and reduce the review of doctors. © 2019 IEEE.

关键词： Intelligent systems

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The Reform and Exploration of Teaching Team in Postgraduate Courses

The Reform and Exploration of Teaching Team in Postgraduate ...

引用

IEEE international conference on computer Science and Educational Informatization (CSEI)

作者： Wenhua Qian Dan Xu Guowu Yuan Wu Hao School of Information Science and Engineering Yunnan University Kunming China

ISBN: (数字)9781728170084

ISBN: (纸本)9781728170091

Postgraduate course teaching plays an important role in postgraduate education. With the development of “double first-class” construction and “new engineering disciplines”, it is imperative to reform the postgraduate course teaching, optimize the teaching system and improve the teaching effect. This paper takes the teaching of “image processing and computer vision” as an example to analyze and research the significance and role of teaching team in postgraduate courses, and discusses the advantages and characteristics of teaching team in the teaching process. We analyze the steps of how to teach the course, such as team building, course preparation, teaching, and assessment, and make a comparative analysis of the teaching effect. This paper summarizes that the teaching team is beneficial to improving the initiative and enthusiasm of students, improving the quality of teaching effectively. In addition, teaching team model can be popularized and applied to other courses.

关键词： image processing computer vision computer science Graphics Training Information science

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Research on Autonomous Driving Perception based on Deep Learning Algorithm 2

Research on Autonomous Driving Perception based on Deep Lear...

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2nd international conference on image and Video processing, and Artificial Intelligence (IPVAI)

作者： Zhou, Bolin Zheng, Jihu Chen, Chen Yin, Pei Zhai, Yang China Automot Technol & Res Ctr Co Ltd Automot Data Ctr Tianjin 300393 Peoples R China Changan Univ Sch Automobile Xian 710000 Shanxi Peoples R China

ISBN: (数字)9781510634107

ISBN: (纸本)9781510634107

Multiple source sensor fusion is the foundation of motion planning for autonomous driving system, which is the crucial part in improving the performances for unmanned operational system. In this article, based on the deep learning platform CATARC constructed, applied with Udacity's Lincoln MKZ multiple sensor data, implemented with Robotic Operation System, computer vision, PointCloud Library, Deep Neural Networks and Extended Kalman Filter, constructed a low-cost object pose estimation data fusion solution, aiming at technic support for the industrialization of autonomous driving technologies.

关键词： Perception Technology Deep Learning image Recognition Point Cloud Recognition Fusion Filtering

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