Multimedia databases

Kalipsiz, Oya

doi:10.1109/iv.2000.859745

Cited by 7 publications

(8 citation statements)

References 9 publications

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“…Multi-modal content retrieval [6,71,74] explores how to store, index, and query multi-modal data [32]. This work explores how to represent unstructured data via structured representations, as we do in our feature generation step.…”

Section: Multi-modal Analytics and Dbmssmentioning

confidence: 99%

Leveraging organizational resources to adapt models to new data modalities

et al. 2020

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As applications in large organizations evolve, the machine learning (ML) models that power them must adapt the same predictive tasks to newly arising data modalities (e.g., a new video content launch in a social media application requires existing text or image models to extend to video). To solve this problem, organizations typically create ML pipelines from scratch. However, this fails to utilize the domain expertise and data they have cultivated from developing tasks for existing modalities. We demonstrate how organizational resources, in the form of aggregate statistics, knowledge bases, and existing services that operate over related tasks, enable teams to construct a common feature space that connects new and existing data modalities. This allows teams to apply methods for data curation (e.g., weak supervision and label propagation) and model training (e.g., forms of multimodal learning) across these different data modalities. We study how this use of organizational resources composes at production scale in over 5 classification tasks at Google, and demonstrate how it reduces the time needed to develop models for new modalities from months to weeks or days.

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Section: Multi-modal Analytics and Dbmssmentioning

confidence: 99%

Leveraging organizational resources to adapt models to new data modalities

et al. 2020

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“…• Text • Graphics: drawing, sketches, and illustrations • Images: color and black & white pictures, photographs, maps and paintings • Animation sequences: animated images or graphic objects • Video: a sequence of images (frames), typically recording a real-life event and usually produced by a video recorder • Audio: generated from an aural recording device • Composite multimedia: a combination of two or more of the above data types [5] Among various media types, media can be divided into two major classes: Continuous and discrete [6]. Media that are changing with time such as audio and video are called continuous media; and time-independent media such as text, still images, and graphics belong to discrete media [6].…”

Section: Definitions: Multimedia Vs Multimedia Databasementioning

confidence: 99%

“…Media that are changing with time such as audio and video are called continuous media; and time-independent media such as text, still images, and graphics belong to discrete media [6].…”

Section: Definitions: Multimedia Vs Multimedia Databasementioning

confidence: 99%

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Multimedia Database Applications: Issues and Concerns for Classroom Teaching

Yu¹,

Brandenburg²

2011

IJMA

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“…That is why managing and querying these large collections of images and alphanumerical information are difficult tasks. The most efficient way for solving these problems is to have a multimedia database management system with the following characteristics (Kalipsiz, 2000, Khoshafian and Baker, 1996, Lu, 1999:…”

Section: Introductionmentioning

confidence: 99%

A Multimedia Database Management System for Medical Data

Stănescu

Burdescu

Brezovan

et al. 2007

Proceedings of the Second International Conference on Signal Processing and Multimedia Applications

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The paper presents a relational multimedia database management system for managing visual and alphanumerical information from the medical domain. The MMDBMS offers numerical and char data types for alphanumerical information, and Image data type used for storing in an original manner the visual information. An Image data type stores the image in a binary manner, its type, its dimensions and information about color and texture that are automatically extracted. This information will be used for content-based visual query process. The color information is represented by the color histogram quantified to 166 colors in the HSV color space. The texture information is represented by a vector with 12 values resulted from the method that uses Gabor filters for texture detection. This DBMS brings up as an element of originality the visual interface for building content-based image query using color and texture characteristics and a modified Select command. This MMDBMS, implemented using Java technologies is platform independent and can be easily used by the medical personnel.

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Multimedia databases

Cited by 7 publications

References 9 publications

Leveraging organizational resources to adapt models to new data modalities

Leveraging organizational resources to adapt models to new data modalities

Multimedia Database Applications: Issues and Concerns for Classroom Teaching

A Multimedia Database Management System for Medical Data

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