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检索条件"任意字段=16th Image Processing: Algorithms and Systems Symposium 2018"

共 650 条记录，以下是131-140 订阅

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Validating few contemporary approaches in image segmentation – A quantitative approach 4th

Validating few contemporary approaches in image segmentation...

引用

4th International symposium on Signal processing and Intelligent Recognition systems, SIRS 2018

作者： Fasiuddin, Syed Blackbuck Engineers Pvt Ltd Hyderabad India

ISBN: (纸本)9789811357572

In this paper, we present an extensive study and quantitative evaluation of six segmentation techniques on images of Berkeley Segmentation Database. image segmentation plays a vital role in many computer vision applications and benchmarking such algorithms may assist research community in present and future research efforts in the field of image segmentation. Color space models, Hybrid color space and wavelet, Gradient Magnitude Techniques, K – means, C-Means & Fuzzy C-Means (FCM) and Edison’s Mean – shift approaches are evaluated using at least six metrics with respect to ground-truth boundaries of entire images in BSD 300/500 dataset images. the results stated here gives useful insights to above mentioned approaches and its significance in aligning upcoming research avenues in image segmentation. © 2019, Springer Nature Singapore Pte Ltd.

关键词： image segmentation

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Microscope image matching in scope of multi-resolution observation system 17

Microscope image matching in scope of multi-resolution obser...

引用

17th image processing: algorithms and systems Conference, IPAS 2019

作者： Putranto, Evan H.E. Usuki, Shin Miura, Kenjiro T. Graduate School of Engineering Shizuoka University Japan Research Institute of Electronics Shizuoka University Japan

Multi-resolution image processing are part of this concept that has a purpose to extracting the detail information of the multi-scale input image. However, in general, to process a multi-scale image there are issue that need to be solved, for an instance color difference, image matching failure, and lack of data which can be observe in a same time. In the same way, observation are work where object of interest are being analyze and being perceive. Observing a multi-resolution image with a lot of object interest would be a daunting task to do. there have been many attempts to match and stitch two or more images into one but still has a chance to get failure. In this article, the author propose a multi-resolution image observation system which are focus on three improvement field successfulness rating of image matching, utilize a classification algorithm to help perceiving object interest and user-friendly interface viewer. On pre-processing, this system take a four type magnification level of image;10 ×, 20 ×, 50 ×, 150 ×. By investigating image matching parameter to stitching group of images, handling false positive of feature point occurred, and then finally arrange and show group of synthesized images inside web application, we believe user can observe microscopic image in a cushioned way. © 2019, Society for Imaging Science and Technology.

关键词： image matching

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Community Detection Based Clustering 16

Community Detection Based Clustering

引用

IEEE 16th International symposium on Intelligent systems and Informatics (SISY)

作者： Luptakova, Iveta Dirgova Pospichal, Jiri Univ SS Cyril & Methodius Dept Appl Informat Fac Nat Sci Trnava 91701 Slovakia

ISBN: (纸本)9781538668412

Community detection is, in principle, a clustering of nodes based typically only on their topological properties that are derived from their positions in the network. Clustering generally uses non-topological information associated with nodes to group them. this paper uses a low-dimensional Euclidean distance of nodes to build a network (i.e. proximity or neighborhood graph) and applies community-based detection for clustering purposes. Nearest neighbors of nodes were connected by edges. Walktrap, edge betweenness, and fast greedy were used for community detection. the proposed approach generally proves superior to basic clustering methods, tested on popular 2D artificial benchmarks, and merits additional study. It also has lower computational complexity than other comparable approaches.

关键词： Benchmark testing Clustering algorithms Indexes image edge detection Detection algorithms Fires Compounds

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Color visibility images and measures of image enhancement 16

Color visibility images and measures of image enhancement

引用

16th image processing: algorithms and systems symposium 2018

作者： Grigoryan, Artyom Agaian, Sos Department of Electrical and Computer Engineering University of Texas at San Antonio United States Computer Science Department College of Staten Island and the Graduate Center Staten IslandNY United States

In this paper, we introduce the human visual system-based several new (a) methods to visualize the very small differences in intensities without big changes of primary image information and (b) measures that quality the visuality of both grayscale and color images. Several illustrative examples are also presented. the proposed concepts can be used for many image processing, computer vision and recognition system applications. © 2018 Society for Imaging Science and Technology.

关键词： image enhancement

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Curvelet based thinning algorithm 4th

Curvelet based thinning algorithm

引用

4th International symposium on Signal processing and Intelligent Recognition systems, SIRS 2018

作者： Jyothi, R.L. Abdul Rahiman, M. College of Engineering Chengannur University of Kerala Thiruvananthapuram India LBS Institute of Technology for Women University of Kerala Thiruvananthapuram India

ISBN: (纸本)9789811357572

Efficiency of a recognition algorithm depends upon availability of noiseless and classes of images with unique and differentiable features. thinning plays an important part in building a recognition system for various types of images. It is mainly used in handwritten character recognition systems and Biometric systems. In Handwritten character recognition systems where there exist large variations within same class of images, thinning plays a vital role. Here curvelet based thinning algorithm is proposed which produces better results compared to other thinning algorithms. the capability of curvelet transform in estimation of directional features added to the strength of proposed work. Curvelet transform is combined with watershed algorithm, binarization and skeletonization to produce the final thinned output. the efficiency of the proposed work has been estimated in this work through detailed experimental analysis and comparisons with 7 efficient thinning algorithms. the measures used for comparison in this works are number of foreground pixels, PSNR (peak signal to noise ratio), MSE (mean square error), RMSE (root mean square error), reduction rate and thinness ratio. © 2019, Springer Nature Singapore Pte Ltd.

关键词： image thinning

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Learning adaptive parameter tuning for image processing 16

Learning adaptive parameter tuning for image processing

引用

16th image processing: algorithms and systems symposium 2018

作者： Dong, Jingming Frosio, Iuri Kautz, Jan UCLA Vision Lab University of California Los AngelesCA United States NVIDIA Santa ClaraCA United States

the non-stationary nature of image characteristics calls for adaptive processing, based on the local image content. We propose a simple and flexible method to learn local tuning of parameters in adaptive image processing: we extract simple local features from an image and learn the relation between these features and the optimal filtering parameters. Learning is performed by optimizing a user defined cost function (any image quality metric) on a training set. We apply our method to three classical problems (denoising, demosaicing and deblurring) and we show the effectiveness of the learned parameter modulation strategies. We also show that these strategies are consistent with theoretical results from the literature. © 2018 Society for Imaging Science and Technology.

关键词： Cost functions

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Rigid and Non-rigid Registration Algorithm Evaluation in MRI for Breast Cancer therapy Monitoring 6th

Rigid and Non-rigid Registration Algorithm Evaluation in MRI...

引用

6th International Conference on Information Technology in Biomedicine (ITIB)

作者： Bzowski, Pawel Danch-Wierzchowska, Marta Psiuk-Maksymowicz, Krzysztof Panek, Rafal Borys, Damian Silesian Tech Univ Inst Automat Control Akad 16 PL-44100 Gliwice Poland Silesian Tech Univ Ctr Biotechnol Krzywoustego 8 PL-44100 Gliwice Poland Nottingham Univ Hosp Darby Rd Nottingham NG7 2UH England

ISBN: (纸本)9783319912110

One of the most common methods in breast cancer radiotherapy planning is Magnetic Resonance Imaging (MRI). It is also used for patient evaluation during treatment because of its sensitivity and lack of ionizing radiation. During each imaging session a patient position can be different and inaccuracies can occur. In this case it is very difficult to compare two image sets originating from different patient examination. the main goals of this work were to implement an algorithm, based on affine transformation with Mutual Information as the quality factor of images match and the method based on the Navier-Lame equation for elastic image co-registration. the rigid transformation is used for the preliminary processing, and the non-rigid transformation allows for successful co-registration of both image sets. Our results were evaluated visually, and the MI indices were calculated. these algorithms allowed for image co-registration in different imaging sessions during the course of treatment.

关键词： MRI image processing image registration Breast imagining

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Dog Breed Identification Using Deep Learning 16

Dog Breed Identification Using Deep Learning

引用

IEEE 16th International symposium on Intelligent systems and Informatics (SISY)

作者： Raduly, Zalan Sulyok, Csaba Vadaszi, Zsolt Zolde, Attila Babes Bolyai Univ Cluj Napoca Romania Codespring Cluj Napoca Romania

ISBN: (纸本)9781538668412

the current paper presents a fine-grained image recognition problem, one of multi-class classification, namely determining the breed of a dog in a given image. the presented system employs innovative methods in deep learning, including convolutional neural networks. Two different networks are trained and evaluated on the Stanford Dogs dataset. the usage/evaluation of convolutional neural networks is presented through a software system. It contains a central server and a mobile client, which includes components and libraries for evaluating on a neural network in both online and offline environments.

关键词： convolutional neural networks dog breed identification fine-grained image recognition image classification Inception-ResNet-v2 mobile trained model Stanford Dogs dataset

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Imputation Using a Correlation-Enhanced Auto-Associative Neural Network with Dynamic processing of Missing Values 16th

Imputation Using a Correlation-Enhanced Auto-Associative Neu...

引用

16th International symposium on Neural Networks (ISNN)

作者： Lai, Xiaochen Wu, Xia Zhang, Liyong Zhang, Genglin Dalian Univ Technol Sch Software Dalian 116620 Peoples R China Dalian Univ Technol Sch Control Sci & Engn Dalian 116624 Peoples R China Dalian Chinacreat Technol Co Ltd Dalian 116021 Peoples R China Key Lab Ubiquitous Network & Serv Software Liaoni Dalian 116620 Peoples R China

ISBN: (纸本)9783030227968;9783030227951

the missing value is a common phenomenon in real-world datasets, which makes the analysis of incomplete data become an active research area. In this paper, a correlation-enhanced auto-associative neural network (CE-AANN) is proposed for imputations of missing values. We design correlation-enhanced hidden neurons and combine them with traditional hidden neurons organically, thereby constructing CE-AANN. Compared with the traditional auto-associative neural network (AANN), the improved architecture can mine cross-correlations among attributes more effectively. the introduction of correlation-enhanced hidden neurons keeps the network from learning a meaningless identity mapping. Moreover, a training scheme named MVPT is used for network training. Missing values are regarded as variables of the loss function and adjusted dynamically based on optimization algorithms. the dynamic processing mechanism takes account of the incompleteness of data during training, which makes the imputation accuracy increase as the training goes further. Experiments validate the effectiveness of the proposed method.

关键词： Incomplete data Missing value imputation Auto-associative neural network Dynamic processing mechanism

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An Efficient Event Detection through Background Subtraction and Deep Convolutional Nets 23rd

An Efficient Event Detection Through Background Subtraction ...

引用

23rd International Computer symposium, ICS 2018

作者： Muchtar, Kahlil Rahman, Faris Munggaran, Muhammad Rizky Juniarta Dwiyantoro, Alvin Prayuda Dharmadi, Richard Nugraha, Indra Chang, Chuan-Yu Nodeflux Jakarta Indonesia Department of Electrical and Computer Engineering Syiah Kuala University Banda AcehAceh Indonesia Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9789811391897

the smart transportation system is one of the most essential parts in a smart city roadmap. the smart transportation applications are equipped with CCTV to recognize a region of interest through automated object detection methods. Usually, such methods require high-complexity image classification techniques and advanced hardware specification. therefore, the design of low-complexity automated object detection algorithms becomes an important topic in this area. A novel technique is proposed to detect a moving object from the surveillance videos based on CPU (central processing units). We use this method to determine the area of the moving object(s). Furthermore, the area will be processed through a deep convolutional nets-based image classification in GPU (graphics processing units) in order to ensure high efficiency and accuracy. It cannot only help to detect object rapidly and accurately, but also can reduce big data volume needed to be stored in smart transportation systems. © Springer Nature Singapore Pte Ltd. 2019.

关键词： image classification

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