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

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A Clothes Classification Method Based on the gcForest 3

A Clothes Classification Method Based on the gcForest

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3rd IEEE international conference on image, vision and Computing, ICIVC 2018

作者： Han, Li Haihong, Zhao Erxin, Yu Yuming, Bai Huiying, Li College of Software Jilin University Changchun Jilin province130012 China College of Computer Science and Technology Jilin University Symbol Computation and Knowledge Engineer of Ministry of Education Jilin University Changchun Jilin province130012 China

ISBN: (纸本)9781538649916

In this paper, we propose a clothes classification method, an application of the gcForest. The gcForest, a novel decision tree ensemble method proposed by Zhou and Feng, performs excellently in many experiments. Moreover, we come up with some adjustment approaches for gcForest. Using these adjustment approaches, we get a satisfactory result when gcForest is used for clothes classification task. Furthermore, we create a data set for clothes classification which contains 8 categories of clothes including a total of 52000 images. And we preprocess the images in the data set by GrabCut-based clothes extraction algorithm. © 2018 IEEE.

关键词： Classification (of information)

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image encryption using chaotic 3-D Arnold’s cat map and logistic map 2nd

Image encryption using chaotic 3-D Arnold’s cat map and log...

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2nd international conference on computer vision and image processing, cvip 2017

作者： Musanna, Farhan Rani, Asha Kumar, Sanjeev Department of Mathematics IIT Roorkee Roorkee India Department of Computer Science and Engineering Indian Institute of Technology Roorkee Roorkee247667 India

ISBN: (纸本)9789811078972

image encryption is different from that of traditional texts or binary data because of some inherent properties of images such as large data capacity, i.e., enormous size and high redundancy (statistical and psycho-visual), making them difficult to handle by traditional methods. In recent years, chaos theory has been explored to find efficient ways to develop secure image cryptosystems. Due to the desirable properties of mixing and sensitivity to initial conditions and parameters (butterfly effect), chaotic systems have found great deal in the domain of image encryption. In this paper, the 2-D chaotic cat map is generalized to its 3-D map counterpart for designing a real-time secure and reliable symmetric encryption design. This new scheme deploys the 3-D Arnold’s cat map to shuffle the positions of image pixels and uses the other chaotic logistic map to perplex the relationship between the plain-image and the cipher-image, thereby significantly enhancing the robustness to differential and statistical attacks. Experimental tests are carried out with comprehensive analysis, demonstrating the high security of the scheme. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Chaotic systems

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A Method for image Co-segmentation with Seeded Foreground

A Method for Image Co-segmentation with Seeded Foreground

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2019 3rd international conference on Machine vision and Information Technology (CMVIT 2019)

作者： Jiaji Wang Zhenjiang Miao Tianyu Zhou Qiang Zhang Miaomiao Li Institute of Information Science School of Computer and Information TechnologyBeijing Jiaotong University

image segmentation is a key technology from image processing to analysis. Without proper segmentation, it is impossible to recognize correctly. In this paper, we propose a method for image co-segmentation based on the biased normalized cuts using a semi-supervised way to deal with foreground regions. In order to take advantage of biased normalized cuts to solve problem, we use 2 D adaptive Wiener filter to smooth the seeded parts of images, then divide images into a set of super-pixels, after that take super-pixels as vertices to form a weighted undirected graph. Thus, the co-segmentation can be seen as an issue of graph partition that solved by biased normalized cuts. The experiments on image data sets show the superior performance of our method.

关键词： image A Method for image Co-segmentation with Seeded Foreground image

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Breast Cancer Detection from Histopathological images Using Deep Learning 3

Breast Cancer Detection from Histopathological Images Using ...

引用

3rd international conference and Workshops on Recent Advances and Innovations in Engineering, ICRAIE 2018

作者： Khuriwal, Naresh Mishra, Nidhi Department of Computer Engineering Poornima University Jaipur Jaipur India

ISBN: (纸本)9781538645253

The cancer is the most dangerous diseases in the world, its mainly effective for women. So, our prime target must be curing the cancer through scientific investigation and the second main target should be early detection of cancer because the early detection of cancer can be helpful for remove the cancer completed. After reviewed 41 papers we found that several techniques are available for cancer detection. In this paperwe proposedDeep Leaning algorithm convolutional neural network for diagnosed breast cancer using Mammograph MIAS database. The paper shows how we can use deep learning technology for diagnosis breast cancer using MIAS Dataset. Because deep learning techniques almost used for high task objective computer vision, image processing, Medical Diagnosis, Neural Language processing. But in this paper, we are applying deep learning technology on the MIAS Database and we have seen that is very beneficial for us for diagnosis breast cancer with accuracy 98%. This paper is divided in three parts first we have collect dataset and applied pre-processing algorithm for scaled and filter data then we have split dataset in training and testing purpose and generate some graph for visualization data. In last implement model on training dataset and achieved accuracy 98%. So, we have seen deep learning technology is a good way for diagnosis breast cancer with MIAS Dataset. This database provides200images and 12 features in the dataset. In this paper we have used 12 features for diagnosis breast cancer that we have got after pre-processing. But before train model we have applied some pre-processing algorithm like Watershed Segmentation, Colour based segmentationand Adaptive Mean Filtersfor scaled dataset then applied model and achieved accuracy. In this paper we also compare deep learning algorithm with other machine learning and seen our proposed system is proved best from others machine learning algorithm. © 2018 IEEE.

关键词： Support vector machines

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Tuberculin skin test checker using digital image processing 3

Tuberculin skin test checker using digital image processing

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3rd international conference on Control and Robotics Engineering, ICCRE 2018

作者： Pedro, John Marnel M. San Barfeh, Davood Pour Yousefian College of Engineering and Computer Studies Lyceum of the Philippines University - Laguna Calamba City Philippines

ISBN: (纸本)9781538666630

The wheal, produced by tuberculin skin tests, was identified by nurses through marking its edges. Four marks will be made and these will be measured - the greatest length of each mark to another mark is considered the size of the wheal. An attempt to imitate the procedure was done by designing a system that can measure the marked sides of the wheal. The implemented system uses an algorithm which locates the four marks in an image. These four marks were measured using the Euclidean distance to determine the distance between each other. Among the 6 edges of the four marks, the one with the greatest length is considered the size of the wheal. Using a scale with a defined size, the pixel value of the greatest length was converted in millimeters. The results showed that the system's measurement is always less than the measurement of the nurse. With an accuracy of 91.53% for the test data, the researcher was able to implement a system that can facilitate in reading the results of tuberculin skin test. © 2018 IEEE.

关键词： Nursing

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A Survey offingertip character identification in open-air using image processing and HCI 3

A Survey offingertip character identification in open-air us...

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3rd international conference for Convergence in Technology (I2CT)

作者： Barhate, Deepti A. Rane, Krunal P. MPSTME SVKMS NMIMS Comp Dept Shirpur India SPPU Sandip Inst Technol & Res Ctr Elect & Telecommun Engn Dept Nasik India

ISBN: (纸本)9781538642733

Finger spelling recognition using finger motion in blaring area is quiet challenging as communicator arc 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 *** 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 *** 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： Finger Spelling Human to-human Comitumication Human computer Interaction Finger motion virtual reality OCR

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A 3D Dual Path U-Net of Cancer Segmentation Based on MRI 3

A 3D Dual Path U-Net of Cancer Segmentation Based on MRI

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3rd IEEE international conference on image, vision and Computing (ICIVC)

作者： He, Yu Yu, Xi Liu, Chang Zhang, Jian Hu, Ke Zhu, Hong Chao Chengdu Univ Coll Informat Sci & Engn Chengdu Sichuan Peoples R China Chengdu Univ Key Lab Pattern Recognit & Intelligent Informat P Chengdu Sichuan Peoples R China Chengdu Univ Res Inst Big Data Chengdu Sichuan Peoples R China Sichuan Normal Univ Sch Phys & Elect Engn Chengdu Sichuan Peoples R China

ISBN: (纸本)9781538649916

Nasopharyngeal Carcinoma (NPC) is one of the most common malignant tumors in China. However, the cancer's region is subtle, variability and irregular. In the traditional diagnostic way, clinicians' diagnosis relies on manual delineations which are time consuming and require rich prior experience. Recently, the deep learning architecture of U-Net and Dual Path Network (DPN) apply well in the biomedical segmentation and nature scene respectively. However, U-Net cannot extract abundance texture information from the data and DPN cannot utilize the information of shallow layer and deep layer closely. Moreover, both of them are applied on the slices of images instead of 3D images directly, which discard the anatomic context in 3D spatial domain. Consequently, this paper proposed a novel 3D convolutional network-Dual Path U-Network (DPU) which integrates U-Net and DPN to segment the cancer's region of NPC automatically. The experiment on the MRI dataset of NPC patients has shown that the DPU is more successful than the corresponding 3D version of U-Net and DPN in the field of 3D biomedical image segmentation automatically.

关键词： 3D convolutional neural networks image segmentation magnetic resoance imaging

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computer Modeling Approach of Leachate Flow in Compacted Laterite Soil Liner 12

Computer Modeling Approach of Leachate Flow in Compacted Lat...

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12th international Civil Engineering Post Graduate conference (SEPKA) / 3rd international Symposium on Expertise of Engineering Design (ISEED)

作者： Yamusa, Yamusa Bello Alias, Noraliani Ahmad, Kamarudin Sa'ari, Radzuan Foong, Loke Kok Univ Teknol Malaysia Fac Civil Engn Skudai 81310 Johor Malaysia Nuhu Bamalli Polytech Dept Civil Engn Zaria 810001 Nigeria

The use of hydraulic barriers in sanitary landfills has become an impeccable means of protecting the groundwater system from leachate. A question to be asked is, can these barriers continue to impede the migration of leachate over a long period? This paper investigates the phenomenon of leachate migration in compacted laterite soil used as liner in sanitary landfills. An experiment was carried out using laterite soil compacted at optimum moisture content using Standard Proctor energy. Leachate was poured on the compacted soil in an acrylic column and its migration was monitored using Digital image Technique (DIT). The DIT capture photographic images at successive intervals of time which were fed through an image processing code to convert them to hue-saturation-intensity (HSI) format with the help of Surfer and Matlab computer softwares. Subsequently, PetraSim computer software was applied to predict the velocity behavior. The predicted velocity value shows that the laterite soil is compatible with the leachate and can be used as soil liner. The outcome of this study would enable designers to use non-destructive method to monitor and predict leachate migration in compacted soil liners to simulates leachate migration in waste containment applications.

关键词： Soils

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Evaluation of business english majors teaching quality based on the attribute importance of rough set 2019

Evaluation of business english majors teaching quality based...

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3rd international Workshop on Education, Big Data and Information Technology, EBDIT 2019

作者： Fan, Yanying Jiang, Suping Zhang, Zimin Chen, Guanping Chen, Yangming Li, Biqing College of Mathematics and Computer Hezhou University Hezhou Guangxi542899 China Guangxi Talent International College Qinzhou Guangxi535000 China College of Tourism and Sports Hezhou University Hezhou542899 China School of Mathematics and Computer Science Hezhou University Hezhou542899 China School of Information and Communication Engineering Hezhou University Hezhou Guangxi542899 China

ISBN: (纸本)9781450372053

Aiming at the unreasonable weight allocation in traditional teaching evaluation, rough set theory (RST) is applied to the process of teaching evaluation. Using the Teaching Quality evaluation data of Business English Majors from Guangxi Talent international College, we establish the evaluation information system, and calculate the importance of evaluation index, based on which, the weight of index is calculated. Finally, the evaluation results are calculated according to the weight of index. The weight of rough set index is determined entirely by the data itself, avoiding the influence of subjective factors, so it is more scientific, reasonable, objective and fair. © 2019 Association for Computing Machinery.

关键词： Rough set theory

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Robust Temporal Super-Resolution for Dynamic Motion Videos

Robust Temporal Super-Resolution for Dynamic Motion Videos

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international conference on computer vision Workshops (ICCV Workshops)

作者： Bumjun Park Songhyun Yu Jechang Jeong Department of Electronics and Computer Engineering Hanyang University Seoul Republic of Korea Department of Electronic Engineering Hanyang University Seoul Republic of Korea

ISBN: (数字)9781728150239

ISBN: (纸本)9781728150246

It is difficult to apply most video temporal super-resolution studies for real-world scenes because they are optimized for a specific range of characteristics. In this paper, we propose a video temporal super-resolution method that is tolerant to motion diversity and noise. Our proposed method improves its robustness by fine-tuning the pre-trained SPyNet that is trained for videos with simple motions and moderate conditions. Moreover, our proposed network learns to accurately synthesize two frames generated by a backward warping function without requiring any additional information using the architecture of a modified DHDN. This enables our proposed method to efficiently synthesize two warped frames by saving the computational complexity for pre-training and extracting the additional information. Finally, we apply the self-ensemble method, which is commonly used in studies on image processing but not on video processing. The application of the self-ensemble method enables our network to generate stable output frames with improved quality without any additional training. Our proposed network proved its performance by ranking 5th in the AIM 2019 video temporal super-resolution challenge; the performance gap between our proposed network and the 3rd-and 4th-ranked solutions was very small. The source code and pre-trained models are available at https://***/BumjunPark/DVTSR.

关键词： Videos Optical flow Training Dynamics Feature extraction Robustness computer architecture

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