Achieving efficient source camera identification on Hadoop

Cattaneo, Giuseppe; Petrillo, Umberto Ferraro; Abate, Andrea F.; Narducci, Fabio; Barra, Silvio

doi:10.1007/s11042-019-7561-0

Cited by 4 publications

(1 citation statement)

References 22 publications

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“…Cattaneo et al [8] investigate the Source Camera Identification problem (i.e., determining the particular digital camera used for taking a given image) on Hadoop, a software framework that provide coding of distributed applications starting from a MapReduce algorithm with little programming efforts.…”

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confidence: 99%

Special issue on information visualisation

Francese

Banissi

Risi

2019

Multimed Tools Appl

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We are in the Big Data era, characterized by an increasing amount of information generated everyday by all the phenomena concerning our life. These data are collected by many information sources and systems ranging from IoT sensors, large databases, social networks and interactive platforms, as well as generic media like images, videos and audios. Thus, to be able to comprehend the phenomena underlying this data there is the need of designing effective visualization tools. The papers selected for this special issue outline and evaluate some recent works on multimedia tools for information visualization and interaction with various types of data, including textual documents, graphs, spatio-temporal data, multimedia contents, and musical data. The international conference on information Visualisation (iV), one of the longest running on the subject has open forum philosophy of interdisciplinary drive to define its subject theme and discussion and focus group. This special issue of Multimedia Tools and Applications for Information Visualisation is based on the handful of submissions to the 22 nd International Conference on Information Visualisation (iV18), which was held in Italy in July 2018. The selected papers give examples of techniques, domains and number of case studies to address some issues. The papers presented in this Special Issue investigate different aspects of the theme highlighted above. The first set of papers [1, 2, 12, 16] investigate and evaluate the visualization of spatial, temporal and spatio-temporal data. Almeida et al. [2] consider how and why consideration of Level of Detail (LoD) plays a crucial role in analytics. They propose a Visual Analytics approach-VAST, allows users to simultaneous inspection of phenomenon using different LoDs. VAST demonstrates using LoDs will reveal different prospective and hence portraying different perception of the phenomenon.

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mentioning

confidence: 99%

Special issue on information visualisation

Francese

Banissi

Risi

2019

Multimed Tools Appl

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Design of ChaApache framework for securing Hadoop application in big data

Gattoju

Nagalakshmi²

2022

Multimed Tools Appl

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Guest editorial: Special issue on information visualisation

Banissi

Huang

2018

Journal of Visual Languages & Computing

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In the current information era, most aspects of life depend on and driven by data, information, knowledge and user experience. The infrastructure of an information-dependent society and drive for new innovation and direction of activities heavily relies on the quality of data, information and analysis of such entities from past to its projected future activities. Information Visualisation, Visual Analytics, Business Intelligence, machine learning and application domains are just a few of the current state of the art developments that effectively enhance understanding of these driving forces. There are several key interdependent determinants emerging that are becoming the focus of scientific activities, such as: raw data (origin, autonomous capture, classification, incompleteness, impurity, filtering), data scale transformation to knowledge acquisition and its dependencies on domain of application. Processing the relationship between these stages, from the raw data to visualisation, has added new impetus to the way these are understood and communicated. Visualisation has been one of the most used methods in presenting data and generating insights [1]. The tradition of use and communication by visualisation is deep rooted and helps us investigate new meanings by application to the humanities, history, art & design, and human factors & user experience studies. Modern day computer assisted analytics and visualisation has added momentum in developing tools that exploit metaphordriven techniques within many applied domains. The techniques are developed beyond visualisation to simplify the complexities, to reveal ambiguity, and to work with incompleteness. The next phase of this evolving field is to understand uncertainty and risk analysis; how this uncertainty is built into the processes that exist in all stages of the process, from raw data to the knowledge acquisition stage.

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Achieving efficient source camera identification on Hadoop

Cited by 4 publications

References 22 publications

Special issue on information visualisation

Special issue on information visualisation

Design of ChaApache framework for securing Hadoop application in big data

Guest editorial: Special issue on information visualisation

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