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检索条件"任意字段=17th Image Processing: Algorithms and Systems Conference, IPAS 2019"

共 249 条记录，以下是121-130 订阅

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An Enhanced Bats Algorithm for Optimization thresholds in Medical image Segmentation 17th

An Enhanced Bats Algorithm for Optimization Thresholds in Me...

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17th International conference on Intelligent Information Hiding and Multimedia Signal processing (IIH-MSP) / 14th International conference on Frontiers of Information Technology, Applications and Tools (FITAT)

作者： Dao, thi-Kien Vu, Ngoc-thanh Nguyen, thi-Xuan-Huong Nguyen, Trong-the Fujian Univ Technol Fujian Prov Key Lab Big Data Min & Applicat Fujian Peoples R China Hai Phong Univ Med & Pharm Haiphong Vietnam Haiphong Univ Management & Technol Haiphong Vietnam VNU HCM Univ Informat Technol Multimedia Communicat Lab Ho Chi Minh City Vietnam Vietnam Natl Univ Ho Chi Minh City 700000 Vietnam

ISBN: (纸本)9789811910531;9789811910524

the key to threshold segmentation is choosing the thresholds that will decide the segmentation's outcome-the calculation complexity increases as the number of thresholds increases, which causes challenges with traditional methods. this study introduces an enhanced bats algorithm (EBA) for selecting optimal picture segmentation thresholds and applies it to the global optimization issue of the segmentation function's objective function. the EBA blends well with picture segmentation that produces exceptional computation in global convergence and robustness and prevents trapping into local optimization. It is particularly well suited to solving complex functions with high dimensions and multiple peaks. Compared to GA and PSO, extensive theoretical study and simulation results reveal that EBA has greater efficacy, efficiency, stability of the range of thresholds, and quality in multi-image and multi-thresholds segmentation.

关键词： Enhanced bats algorithm Kapur entropy Optimization algorithms Picture threshold segmentation

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Parameter assisted HE colored tissue image classification

Parameter assisted HE colored tissue image classification

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17th IEEE International conference on Intelligent Engineering systems, INES 2013

作者： Kozlovszky, M. Hegedus, K. Szenasi, S. Kiszler, G. Wichmann, B. Bandi, I. Eigner, Gy. Sas, P.I. Kovacs, L. Garaguly, Z. Jonas, V. Kiss, G. Valcz, G. Molnar, B. Biotech Laboratory Obuda University Budapest Hungary 2nd Department of Internal Medicine Semmelweis University Budapest Hungary Molecular Medicine Research Unit Hungarian Academy of Sciences Budapest Hungary

ISBN: (纸本)9781479908288

the aim of our work was to design and implement a software solution, which supports quantitative histological analysis of hematoxilin eozin (HE) stained colon tissue samples, identify tissue structures - nuclei, glands and epithelium - using image processing methods. Furthermore, based on the result of the histological segmentation, it gives a suggestion for the negative or malignant status of the samples automatically. In this paper we describe the algorithm which builds up mainly by two software components: MorphCheck -our software framework-, which is capable to make effective, morphometric evaluation of high resolution digital tissue images and a modified WND-CHARM (Weighted Neighbor Distance Using Compound Hierarchy of algorithms Representing Morphology), which is a multi-purpose image classifier. the image classification was performed mainly based on 75+15 pre-defined colon tissue specific parameters, which were measured by MorphCheck, and other 2873 in-built generic image parameters, which were measured by WND-CHARM. We appended WND-CHARM's learning and classification capabilities with our colon tissue specific parameters and with this act we have increased its classification accuracy significantly on HE stained colon tissue sample images. © 2013 IEEE.

关键词： image classification

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Designing an Affordable System for Early Defect Detection Using image processing 17

Designing an Affordable System for Early Defect Detection Us...

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17th International conference on Manufacturing Research, ICMR 2019, incorporating the 34th National conference on Manufacturing Research, NCMR 2019

作者： Puneeth K.s. Sahay, Atul Shreya G.h. Biswas, Pradipta Arora, Manish Chakrabarti, Amaresh Centre for Product Design and Manufacturing Indian Institute of Science Bengaluru560012 India

ISBN: (纸本)9781643680088

the affordability of high technology inspection systems for Micro, Small and Medium Enterprises (MSME) is a big challenge since, if not implemented, it will affect productivity and quality of the product. A case study has been carried out to understand inspection practices at an MSME in India (at an orthotic footwear company), within its medical device industry where safety and risk management are critical. Raw materials are not inspected during the initial stages of production, due to which the whole product is rejected if any defect is subsequently found. Due to this rejection, manufacturing time and man hours are squandered at the expense of quality. To enable early inspection that is also economical, existing methodology is integrated to develop a system that can boot from a Next Unit Computing (NUC) with real time processing. the inspection system uses Fault Detection and Isolation (FDI) technique using 'canny edge detection algorithm' for image processing;defects are identified as blobs by convolving the image matrix. the images are captured by low cost off-the-shelf cameras arranged in-line perpendicular to the bespoke set up. A set of light sources is used for illumination and the algorithm is evaluated for its accuracy under different light conditions. © 2019 the authors and IOS Press. All rights reserved.

关键词： Inspection

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Cluster storage systems gotta have HeART: improving storage efficiency by exploiting disk-reliability heterogeneity 17

Cluster storage systems gotta have HeART: improving storage ...

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17th USENIX conference on File and Storage Technologies (FAST)

作者： Kadekodi, Saurabh Rashmi, K. V. Ganger, Gregory R. Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781939133090

Large-scale cluster storage systems typically consist of a heterogeneous mix of storage devices with significantly varying failure rates. Despite such differences among devices, redundancy settings are generally configured in a one-scheme-for-all fashion. In this paper, we make a case for exploiting reliability heterogeneity to tailor redundancy settings to different device groups. We present HeART, an online tuning tool that guides selection of, and transitions between redundancy settings for long-term data reliability, based on observed reliability properties of each disk group. By processing disk failure data over time, HeART identifies the boundaries and steady-state failure rate for each deployed disk group (e.g., by make/model). Using this information, HeART suggests the most space-efficient redundancy option allowed that will achieve the specified target data reliability. Analysis of longitudinal failure data for a large production storage cluster shows the robustness of HeART's failure-rate determination algorithms. the same analysis shows that a storage system guided by HeART could provide target data reliability levels with fewer disks than one-scheme-for-all approaches: 11-16% fewer compared to erasure codes like 10-of-14 or 6-of-9 and 33% fewer compared to 3-way replication.

关键词： Redundancy

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Enhancing Efficiency and Quality of image Caption Generation with CARU 17th

Enhancing Efficiency and Quality of Image Caption Generation...

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17th International conference on Wireless algorithms, systems, and Applications (WASA)

作者： Huang, Xuefei Ke, Wei Sheng, Hao Macao Polytechn Univ Fac Sci Appl Macau Peoples R China Macao Polytechn Univ Engn Res Ctr Appl Technol Machine Translat & Arti Minist Educ Macau Peoples R China Beihang Univ Sch Comp Sci & Engn State Key Lab Virtual Real Technol & Syst Beijing 100191 Peoples R China Beihang Hangzhou Innovat Inst Yuhang Hangzhou 310023 Peoples R China

ISBN: (纸本)9783031192135;9783031192142

image caption is textual explanation automatically generated by a computer according to the content in an image. It involves both image and natural language processing, and thus becomes an important research topic in pattern recognition. Deep learning has been successful in accomplishing this task, and the quality of captions generated by existing methods is already high. However, due to the broadness and variety of image caption applications, the current generated captions are still not sufficiently detailed, and the training efficiency can also be improved. therefore, under the encoder-decoder framework of deep learning, how to use fewer parameters to improve the training efficiency and retain the quality of the generated image descriptions is a huge challenge. In this work, we introduce an improved method based on the encoder-decoder structure, adding an attention mechanism, and applying the content adaptive recurrent unit (CARU), as the decoder, to generate image captions. Inspired by GRU, CARU is designed to have comparable performance with fewer parameters, and is sensitive to the features in hidden layers. the experimental results show, based on MsCOCO dataset, the proposed method achieved better performance than that using GRU as the decoder, and took less training time, effectively improves the training efficiency.

关键词： image caption generation Content adaptive recurrent unit Feature extraction Deep learning Training efficiency

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6th International conference on Database and Expert systems Applications, DEXA 1995

6th International Conference on Database and Expert Systems ...

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6th International conference on Database and Expert systems Applications, DEXA 1995

ISBN: (纸本)9783540603030

the proceedings contain 61 papers. the special focus in this conference is on Object-Oriented Databases and Advanced Database Applications. the topics include: Communication costs in digital library databases;METU object-oriented DBMS kernel;gaining a uniform view of different integration aspects in a prototyping environment;a frame-based approach for interoperation support in multidatabase systems;developing distributed database applications using TSL;prints of the 17th century in a distributed digital library system;a class definition language;design and implementation of object-oriented views;a visual object-oriented query language for geographic information systems;capturing essential questions using question support facilities in the VIEW classroom;a fuzzy model of managerial decision making incorporating risk and ambiguity aversion;people oriented software technology, and its use in environmental reporting;a cost evaluator for parallel database systems;a performance study of declustering strategies for parallel spatial databases;benchmarking object-oriented database systems for CAD;combining reverse with forward database engineering;performance evaluation for clustering algorithms in object-oriented database systems;applied active databases for evolving image processing algorithms;spatial reasoning for GIS using a tesseral data representation;a new dynamic signature file method in parallel processing environment;general protocols for consensus in distributed systems;the multiple representation in an architectural application;simulation of schema change using views;a depository for structured text objects;issues on hypertext design;disjunctive ordered logic and an algebraic rewriting theorem of multiple linear recursions and its applications.

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Human intervention in automated decision-making: Toward the construction of contestable systems 19

Human intervention in automated decision-making: Toward the ...

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17th International conference on Artificial Intelligence and Law (ICAIL)

作者： Almada, Marco Univ Sao Paulo Sao Paulo Brazil Lawgorithm Sao Paulo Brazil

ISBN: (纸本)9781450367547

Concerns about "black box" machine learning algorithms have influenced why modern data protection laws and regulations on their establishment of a right to human intervention on decision-making supported by artificial intelligence. Such interventions provide data subjects with means to protect their rights, freedoms, and legitimate interests, either as a bare minimum requirement for data processing or as a central norm governing decision-aiding artificial intelligence. In this paper, I present contestability by design as an approach to two kinds of issues with current legal implementations of the right to human intervention. the first kind is the uncertainty about what kind of decision should be covered by this right: should intervention be restricted to those decisions with no human involvement, or should it be interpreted in a broader sense, encompassing all decisions that are effectively shaped by automated processing? the second class of issues ensues from practical limitations of this right to intervention: even within a clear conceptual framework, data subjects might still lack the information they need to the concrete exercise of their right, or the human intervention itself might introduce biases and limitations that result in undesirable outcomes. After discussing how those effects can be identified and measured, I then advance the thesis that proper protection of the rights of data subjects is feasible only if there are means for contesting decisions based solely on automated processing is not an afterthought, but instead a requirement at each stage of an artificial intelligence system's lifecycle.

关键词： Automated decision-making algorithmic bias machine learning regulation contestability by design privacy by design

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Breast MRI tumour segmentation using modified automatic seeded region growing based on particle swarm optimization image clustering 17

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17th Online World conference on Soft Computing in Industrial Applications, WSC17

作者： Al-Faris, Ali Qusay Ngah, Umi Kalthum Isa, Nor Ashidi Mat Shuaib, Ibrahim Lutfi Universiti Sains Malaysia Penang Malaysia Universiti Sains Malaysia Penang Malaysia

ISBN: (纸本)9783319009292

In this paper, a segmentation system with a modified automatic Seeded Region Growing (SRG) based on Particle Swarm Optimization (PSO) image clustering will be presented. the paper is focused on Magnetic Resonance Imaging (MRI) breast tumour segmentation. the PSO clusters’ intensities are involved in the proposed algorithms of the automated SRG initial seed and threshold value selection. Prior to that, some pre-processing methodologies are involved. And breast skin is detected and deleted using the integration of two algorithms, i.e. Level Set Active Contour and Morphological thinning. the system is applied and tested on the RIDER breast MRI dataset, and the results are evaluated and presented in comparison to the Ground Truths of the dataset. the results show higher performance compared to the previous segmentation approaches that have been tested on the same dataset. © Springer International Publishing Switzerland 2014.

关键词： Magnetic resonance imaging

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Digital watermarking method based on image compression algorithms 17th

Digital watermarking method based on image compression algor...

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17th International conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and systems, NEW2AN 2017, 10th conference on Internet of things and Smart Spaces, ruSMART 2017 and 3rd International Workshop on Nano-scale Computing and Communications, NsCC 2017

作者： Bezzateev, Sergey Voloshina, Natalia Saint-Petersburg University of Aerospace Instrumentation St. Petersburg Russia ITMO University St. Petersburg Russia

ISBN: (纸本)9783319673790

Digital watermarking is an efficient method for digital access rights management utilized in the scope of multimedia data. A possibility to combine the procedure of compression and watermarking in effective way for digital images is proposed in this manuscript. this research is focused on the compression methods considering the significance of the initial multimedia object (for example image) different elements to increase the quality of process (compressed) image. One of the most effective approaches for this task is to utilize Error Correcting Codes (ECC) allowing to maintain the number of resulting errors (distortion) as well as the value of resulting compression ratio. the application of such codes enables to distribute errors that are added during the processing procedure according to predefined significance of the initial multimedia object elements. the approach based on Weighted Hamming Metric guarantying the limitation of maximum errors (distortions) with predefined significance is represented as an example. © 2017, Springer International Publishing AG.

关键词： image compression

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Restoration of images of social networks that have undergone processing, on the example of the social network Instagram 5

Restoration of images of social networks that have undergone...

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Data Science Session at the 5th International conference on Information Technology and Nanotechnology, DS-ITNT 2019

作者： Khotilin, M.I. Kravtsova, N.S. Kupriyanov, A.V. Paringer, R.А. Samara National Research University Moskovskoe Shosse 34А Samara443086 Russia Image Processing Systems Institute of RAS Branch of the FSRC "Crystallography and Photonics" RAS Molodogvardejskaya street 151 Samara443001 Russia

this paper is devoted to finding the source images for the processed images of social networks. Existing methods and approaches that take place in the performance of this task are considered. the algorithms of image r... 详细信息

关键词： image reconstruction

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