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A MULTI-CLUSTERING FUSION SCHEME FOR DATA PARTITIONING

DIMITRIOS S. FROSSYNIOTIS, CHRISTOS PATERITSAS, ANDREAS STAFYLOPATIS
2005 International Journal of Neural Systems  
A multi-clustering fusion method is presented based on combining several runs of a clustering algorithm resulting in a common partition.  ...  Subsequently, a fusion procedure is applied to the clusters generated during the previous 1 phase to determine the optimal number of clusters in the data set according to some predefined criteria.  ...  The present work, following an approach analogous to the latter schemes, proposes a multi-clustering fusion method which tackles the above two important problems and is able to partition a data set in  ... 
doi:10.1142/s0129065705000360 pmid:16278943 fatcat:w746l3vqy5d5pfof4oeapjheoe

A Multi-clustering Fusion Algorithm [chapter]

Dimitrios Frossyniotis, Minas Pertselakis, Andreas Stafylopatis
2002 Lecture Notes in Computer Science  
A multi-clustering fusion method is presented based on combining several runs of a clustering algorithm resulting in a common partition.  ...  Experiments using both simulated and real data sets indicate that the multi-clustering fusion algorithm is able to partition a set of data points to the optimal number of clusters not constrained to be  ...  Fig. 1 . 1 Lith data set after the Partitioning procedure (multi-fusionk-means). Fig. 2 . 2 Lith data set after the Fusion procedure (multi-fusion-kmeans).  ... 
doi:10.1007/3-540-46014-4_21 fatcat:oe5ompfbirbwxcgh2cr6gcmnva

A Study on Cluster Partitioning with Cooperative MISO Scheme in Wireless Sensor Networks

Zheng Huang, Hiraku Okada, Masaaki Katayama, Takaya Yamazato
2012 International Journal of Distributed Sensor Networks  
Both single-hop and multihop transmissions with cooperative Multi-Input Single-Output (MISO) scheme are considered for the intercluster communications.  ...  Besides, uniform and linear data fusions are discussed. Then, the calculations of energy consumptions are derived.  ...  Using a cooperative transmitting (Multi-Input Single-Output, MISO) scheme, Bai et al.  ... 
doi:10.1155/2012/490823 fatcat:ochrgcijhrb5bpd6ejn5ucw6re

Optimal Cluster Partitioning for Wireless Sensor Networks with Cooperative MISO Scheme

Zheng Huang, Takaya Yamazato, Masaaki Katayama
2010 2010 Sixth Advanced International Conference on Telecommunications  
Both single-hop and multi-hop transmissions with cooperative Multi-Input Single-Output (MISO) scheme are considered for inter-cluster communications.  ...  The paper discusses the optimal cluster partitioning for wireless sensor networks deployed in continuous areas.  ...  As for a multi-hop scheme, the data of source clusters will be relayed by other clusters, while in a single-hop scheme the data will be transmitted to the BS directly.  ... 
doi:10.1109/aict.2010.67 dblp:conf/aict/HuangYK10 fatcat:dfof246k5rftxha4dyti6cnlhi

An Adaptable Gaussian Neuro-Fuzzy Classifier [chapter]

Minas Pertselakis, Dimitrios Frossyniotis, Andreas Stafylopatis
2003 Lecture Notes in Computer Science  
The novelty of the model lies in a flexible and efficient initialization technique that first partitions the data space utilizing Gaussian distributions and then merges clusters so as to produce an effective  ...  Our approach describes a model that operates as a selfevaluating classifier using on-line re-clustering, addressing adequately the basic issues of modern demands.  ...  Similarly, using the proposed multi-clustering gaussian fusion algorithm for partitioning and for initializing the classifier will be referred to as Multi-Fusion-SuPFuNIS.  ... 
doi:10.1007/3-540-44989-2_110 fatcat:mq6zg5ps2vbpxj342vvza4dwrq

A general framework for depth compression and multi-sensor fusion in asymmetric view-plus-depth 3D representation

Mihail Georgiev, Evgeny Belyaev, Atanas Gotchev
2020 IEEE Access  
Such segmentation allows for a corresponding depth segmentation, decimation and reconstruction with varying quality and is instrumental in tasks such as depth compression and 3D data fusion.  ...  We demonstrate that our scheme is especially applicable for low bit-rate depth encoding and for fusing color and depth data, where the latter is noisy and with lower spatial resolution.  ...  , Section IV describes application realizations for depth encoding and 3D fusion of asymmetric V+Z sensor data utilizing a proposed multi-layer congruent super-pixel clustering mechanism, Section V provides  ... 
doi:10.1109/access.2020.2996689 fatcat:ula7xd5k7rdjbfgv4chixzsdgm

Formation of Fused Images of the Land Surface from Radar and Optical Images in Spatially Distributed On-Board Operational Monitoring Systems

Vadim A. Nenashev, Igor G. Khanykov
2021 Journal of Imaging  
algorithm, which produces many partitions into clusters.  ...  This paper considers the issues of image fusion in a spatially distributed small-size on-board location system for operational monitoring.  ...  Data Availability Statement: All data supporting reported results are public. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/jimaging7120251 pmid:34940718 pmcid:PMC8705870 fatcat:xkindvton5cy7mirz4cepkgene

A divide-and-conquer method for multi-net classifiers

D. Frosyniotis, A. Stafylopatis, A. Likas
2003 Pattern Analysis and Applications  
Two clustering methods have been applied for input space partitioning and two schemes have been considered for combining the outputs of the multiple classifiers.  ...  In this work, we present and test a pattern classification multi-net system based on both supervised and unsupervised learning.  ...  The present work introduces a different approach for building a multi-net classifier system.  ... 
doi:10.1007/s10044-002-0174-6 fatcat:h7372gqgqvbhjjbomua4mf2pf4

A Novel Approach for Cluster Head Selection using Trust Function in WSN

Vipul Narayan, A. K. Daniel
2021 Scalable Computing : Practice and Experience  
The nodes are scattered randomly in RoI (Region of Interest) and data is transmitted to Base Station (BS) using the multi-hop technique.  ...  The data fusion method based on the trust function is used to get accurate data in the second stage. The energy model is utilized to reduce the excessive energy transmission inside the network.  ...  In [19] proposed a protocol in which WSN is partitioned into equal size regions and static clustering scheme is used to avoid the overhead problem and multi-hop scheme for transfer the data to the BS  ... 
doi:10.12694/scpe.v22i1.1808 fatcat:xxnlfddwcrgutjlyf4d5iwuo7y

Multi-focus Image Fusion Based on Similarity Characteristics [article]

Ya-Qiong Zhang, Xiao-Jun Wu, Hui Li
2022 arXiv   pre-print
A novel multi-focus image fusion algorithm performed in spatial domain based on similarity characteristics is proposed incorporating with region segmentation.  ...  In this paper, a new similarity measure is developed based on the structural similarity (SSIM) index, which is more suitable for multi-focus image segmentation.  ...  0.5134 Table 2 : 2 Performance for Different Fusion Schemes with Fig.8 Table 1 : 1 Performance for Different Fusion Schemes with Fig.7 Table 3 : 3 Performance for different fusion schemes Table  ... 
arXiv:1912.07959v2 fatcat:bttcxwivevc5zpcsr6dlqfibpq

Multi-view Clustering via Deep Matrix Factorization and Partition Alignment [article]

Chen Zhang, Siwei Wang, Jiyuan Liu, Sihang Zhou, Pei Zhang, Xinwang Liu, En Zhu, Changwang Zhang
2021 arXiv   pre-print
To solve the above issues, we propose a novel multi-view clustering algorithm via deep matrix decomposition and partition alignment.  ...  To be specific, the partition representations of each view are obtained through deep matrix decomposition, and then are jointly utilized with the optimal partition representation for fusing multi-view  ...  Finally, we unify the base partition learning and late fusion into a unified framework, hoping to learn a consensus partition matrix for clustering.  ... 
arXiv:2105.00277v2 fatcat:hp4ou4bkrnh45pioutpvuz5iru

BJTU TRECVID 2007 Video Search

Shikui Wei, Yao Zhao, Zhenfeng Zhu, Nan Liu, Yufeng Zhao, Fang Wang, Xie Lin
2007 TREC Video Retrieval Evaluation  
In order to bring up true relevant results, a multi-view based reranking method is employed for reordering the search results derived from run F_A_1_JTU_FA_1_1.  ...  The following five runs test the effect on reranking performance of different combination of clustering methods and fusion strategies.  ...  To have more high precision on top-ranked results, a multi-view based scheme is proposed for reordering top N initial results.  ... 
dblp:conf/trecvid/WeiZZZLZZWL07 fatcat:zctwxq6ogrb2jepzprnuy6ppy4

Gene prioritization and clustering by multi-view text mining

Shi Yu, Leon-Charles Tranchevent, Bart De Moor, Yves Moreau
2010 BMC Bioinformatics  
In such case, multi-view text mining is a superior and promising strategy for text-based disease gene identification.  ...  In particular, it can help identify the most interesting candidate genes for a disease for further experimental analysis.  ...  SY performed text mining, programmed the algorithms, analyzed the data and wrote the paper.  ... 
doi:10.1186/1471-2105-11-28 pmid:20074336 pmcid:PMC3098068 fatcat:rja5rhssdrcsxd4xxsosux7sjq

Disjoint multi mobile agent itinerary planning for big data analytics

Bo Liu, Jiuxin Cao, Jie Yin, Wei Yu, Benyuan Liu, Xinwen Fu
2016 EURASIP Journal on Wireless Communications and Networking  
In this paper, we design a routing itinerary planning scheme for the multi-agent itinerary problem by constructing the spanning tree of WSN nodes.  ...  Sensor networks are often part of a cyber-physical system. A large-scale sensor network often involves big data collection and data fusion.  ...  The clustering mechanism and multi-path mechanism are different representative algorithms for data collection in a WSN.  ... 
doi:10.1186/s13638-016-0607-3 fatcat:f4tiuzwinnfn5bor3zpb6nexre

Distributed Training and Inference of Deep Learning Models for Multi-Modal Land Cover Classification

Maria Aspri, Grigorios Tsagkatakis, Panagiotis Tsakalides
2020 Remote Sensing  
Spark Cluster.  ...  Experimental results also demonstrate that proposed model parallelization schemes achieve more efficient resource use and more accurate predictions compared to data parallelization approaches.  ...  the data used in this study, and the IEEE GRSS Image Analysis and Data Fusion Technical Committee.  ... 
doi:10.3390/rs12172670 fatcat:amoqucrxdzez5nejfp2iajs2o4
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