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Survey on Video Big Data: Analysis Methods and Applications

P. Ushapreethi, G.G. Lakshmipriya
2017 International Journal of Applied Engineering Research  
In this big data era, Video data face its new challenges to store and retrieve, since the size of video data is high and the processing and analysis methods are very complex.  ...  In recent years, Big Data has become high-focus of researchers as many organizations have been processing huge amount of information.  ...  INTRODUCTION In this big data era, Video big data storage and retrieval has its own particularities.  ... 
doi:10.37622/ijaer/12.10.2017.2221-2231 fatcat:ghhxte6fkfdipesh4osdlmj224

Annotation Based Image Retrieval using GMM and Spatial Related Object Approaches

Monica Hidajat
2015 International Journal of Control and Automation  
Image annotation and retrieval has been a popular research topic for decades.  ...  In this study, an attempt to use a Gaussian Mixture Model (GMM) based approach and spatial related information of the annotated objects has been performed in order to improve the performance of the ABIR  ...  Santika for his fruitful discussion throughout the supervision process. This research use dataset from LAMDA (http://lamda.nju.edu.cn/).  ... 
doi:10.14257/ijca.2015.8.8.37 fatcat:k2jrnlir2jfn7gtpq4nthqna2e

Model-based Big Data Analytics-as-a-Service: Take Big Data to the Next Level

Claudio Agostino Ardagna, Valerio Bellandi, Michele Bezzi, Paolo Ceravolo, Ernesto Damiani, Cedric Hebert
2018 IEEE Transactions on Services Computing  
Index Terms-Big Data, Model-Driven Architecture, OWL-S ! • C.A. Ardagna, V. Bellandi, P. Ceravolo are with the  ...  The opacity and variety of Big Data technologies and computations, in fact, make BDA a failure prone and resource-intensive process, which requires a trial-and-error approach.  ...  Such transformations are implemented in a methodology specifying a semi-automatic process for MBDAaaS (Sections 4 and 5).  ... 
doi:10.1109/tsc.2018.2816941 fatcat:wcuuqwwnmzf3zpjkpzm7sgcnsy

Classification and Automatic Annotation Extension of Images Using Bayesian Network [chapter]

Sabine Barrat, Salvatore Tabbone
2008 Lecture Notes in Computer Science  
Besides the automatic annotation extension with our model for images with missing keywords outperforms the visual-textual classification by 6.8%.  ...  In many vision problems, instead of having fully annotated training data, it is easier to obtain just a subset of data with annotations, because it is less restrictive for the user.  ...  A Gaussian-Mixtures and Multinomial mixture model We present a hierarchical probabilistic model of multiple-type data (images and associated keywords) in order to classify large annotated image databases  ... 
doi:10.1007/978-3-540-89689-0_97 fatcat:mzrq6dvvanh7bmnwdffnucrwpi

A note on exploration of IoT generated big data using semantics

Rajiv Ranjan, Dhavalkumar Thakker, Armin Haller, Rajkumar Buyya
2017 Future generations computer systems  
activation (SA) algorithm and the ontology model in order to promote the associative retrieval of big data.  ...  Associative retrieval, on the other hand, has been identified as a potential technique for big data.  ... 
doi:10.1016/j.future.2017.06.032 fatcat:nc3gui7mwrcp3djzzvbugzjorm

OMNIS/2: A Multimedia Meta System for Existing Digital Libraries [chapter]

Günther Specht, MichaelG. Bauer
2000 Lecture Notes in Computer Science  
Thus with OMNIS/2, even mere retrieval systems -and nowadays most digital library systems are mere retrieval systems -can be enriched to interactive multimedia DL-systems and are combined into one virtual  ...  Since today more and more complementary information is available in different electronic media there is an increasing demand for the integration of traditional digital library systems and multimedia systems  ...  This is a big advantage over methods which require an explicit assignment of topics for each document.  ... 
doi:10.1007/3-540-45268-0_17 fatcat:wkhcwsccv5afjheh7km25hx3r4

Content based Caption Generation for Images Embedded in News Articles

Amit KumarKohakade, Emmanuel M
2014 International Journal of Computer Applications  
In current digital world Content based Image retrieval is becoming critical problem as size of data on Internet increasing rapidly.  ...  On other hand by image processing we find out who's in picture as it helps in making accurate caption by using face recognition and it will increase image retrieval.  ...  Also thankful of IIT Kanpur and AT&T for providing open access for face database..  ... 
doi:10.5120/17567-8231 fatcat:kib4kcrf2jckzfrn4s6u5wh6ym

Automatic Ground Truth Generation of Camera Captured Documents Using Document Image Retrieval

Sheraz Ahmed, Koichi Kise, Masakazu Iwamura, Marcus Liwicki, Andreas Dengel
2013 2013 12th International Conference on Document Analysis and Recognition  
Novelty of the proposed approach lies in the use of document image retrieval for automatic labeling, especially for camera captured documents, which contain different distortions specific to camera, e.g  ...  In this paper a novel method for automatic ground truth generation of camera captured document images is proposed. Currently, no dataset is available for camera captured documents.  ...  [7] used degradation models to synthetic data in different languages, for building datasets which can be used for training and testing of scanned documents.  ... 
doi:10.1109/icdar.2013.111 dblp:conf/icdar/AhmedKILD13 fatcat:ametowhrebdarabfpx5dbh7qmq

Music Classification Method Using Big Data Feature Extraction and Neural Networks

Xiabin Li, Jin Li, Zhao Kaifa
2022 Journal of Environmental and Public Health  
It would be inefficient and unrealistic to attempt to classify music using manual labelling in the age of big data. Feature extraction and neural networks are the tools employed in this paper.  ...  People cannot easily search for the desired music without classifying enormous music resources and developing a successful music retrieval system.  ...  In machine learning, we commonly refer to it as a model. is paper provides a definition of big data based on ongoing research in the field: big data requires a new processing mode to have a significant  ... 
doi:10.1155/2022/5749359 fatcat:4gwu572sg5fqtoyycxvyw4odaa

Editorial for the Special Issue on MICCAI 2015

Nassir Navab, Alejandro F. Frangi, William Wells, Andreas Maier
2016 Medical Image Analysis  
Lê et al. develop an approach based on Gaussian Process models that can provide samples from a distribution on segmentations from a single example.  ...  Big data, particularly in the context of image analytics over large-scale image or multimodal databases has increasingly attracted the attention of our research community as evidenced by several of the  ... 
doi:10.1016/j.media.2016.09.007 pmid:27692242 fatcat:ibfcfdwyjbg6pdzvhys6wekzaa

Application of Gauss Mutation Genetic Algorithm to Optimize Neural Network in Image Painting Art Teaching

Weiming Xing, Jian Zhang, Quan Zou, Jun Lin, Bai Yuan Ding
2021 Computational Intelligence and Neuroscience  
In the future research in the field of art industry, neural network will optimize the teaching cloud platform technology, which has laid a solid foundation for improving students' aesthetic quality and  ...  We use Gaussian mutation genetic algorithm to study the neural network optimized teaching cloud platform technology.  ...  Based on genetic algorithm, they carry out data processing and model prediction for complex problems [24] . en, the genetic algorithm is used to optimize various neural networks and applied in the field  ... 
doi:10.1155/2021/3302617 pmid:34824577 pmcid:PMC8610699 fatcat:fmvi6bknlzaaxcdiqpzvzy3phe

State of the art in image processing & big data analytics: issues and challenges

S Vahini Ezhilraman, Sujatha Srinivasan
2018 International Journal of Engineering & Technology  
In turn, Big Data analytics for mining knowledge from data created through image processing techniques has a huge potential in sectors like education, government organizations, healthcare institutions,  ...  The resultant output by most image processing techniques creates a huge amount of data which is categorized as Big-data.  ...  Sujatha Srinivasan, HOD, Dept. of IT, VISTAS, for her effective and patient full guidance to complete this paper. I am also thankful to the VISTAS for giving me opportunity to carry my research.  ... 
doi:10.14419/ijet.v7i2.33.13885 fatcat:jmfe3uzgobclhl6qdbkslwc6ai

Intelligent Big Information Retrieval of Smart Library Based on Graph Neural Network (GNN) Algorithm

Lu Pang, Qiangyi Li
2022 Computational Intelligence and Neuroscience  
In order to provide users with more humanized and intelligent big data knowledge services, a research method of intelligent big information retrieval of Smart Library Based on graph neural network (GNN  ...  data knowledge services.  ...  algorithm, this paper proposes an automatic encoder system of graph neural network algorithm based on motif to better realize the intelligent big information retrieval of Smart Library [1] .  ... 
doi:10.1155/2022/1475069 pmid:35875784 pmcid:PMC9300356 fatcat:t4hyizfsavgqjften7mckclrmu

Telefonica Research System for the Spoken Web Search task at Mediaeval 2012

Xavier Anguera
2012 MediaEval Benchmarking Initiative for Multimedia Evaluation  
The second system also uses a DTW-like approach but allowing for all reference files o be searched at once using an information retrieval approach.  ...  With these frames we train a one Gaussian silence model and with the rest we train a 4-Gaussian speech model.  ...  In our systems we use Gaussian posteriors obtained from a GMM model that has been trained on all available reference data (i.e. development and testing data).  ... 
dblp:conf/mediaeval/Anguera12 fatcat:re7b4wywona4fdocpi46cud3pe

An Information Reinstatement Dealing with Machine Learning
Dr., Dr

Firoj Parwej, Hani Alquhayz
2016 Transactions on Machine Learning and Artificial Intelligence  
The process of machine learning is similar to that of data mining. Both systems search through data to look for patterns.  ...  For instance, the best HMM configuration over TIMIT reaches 93.90% AUC, compared to 96.30% for the best Discriminative Gaussian Mixture Model spotter.  ...  Digital technologies give a unified infrastructure to store, exchange and automatically process big document collections.  ... 
doi:10.14738/tmlai.41.1691 fatcat:ariidkmccrhuvdo6zoxn7dsxgi
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