Efficient retrieval of trademark images from large databases

2021 ◽  
Vol 11 (2) ◽  
pp. 165
Author(s):  
Akriti Nigam ◽  
Vivek Kumar Singh
Keyword(s):  
Large Databases ◽  
Efficient Retrieval ◽  
Trademark Images

Efficient retrieval of trademark images from large databases

2021 ◽  
Vol 11 (2) ◽  
pp. 165
Author(s):  
Akriti Nigam ◽  
Vivek Kumar Singh
Keyword(s):  
Large Databases ◽  
Efficient Retrieval ◽  
Trademark Images

Data Mining-Based CBIR System

2018 ◽  
pp. 440-457
Author(s):  
Shruti Kohli ◽  
Vijay Shankar Gupta
Keyword(s):  
Data Mining ◽  
Social Network Sites ◽  
Image Databases ◽  
Multimedia Data ◽  
Content Based Image Retrieval ◽  
The Internet ◽  
Multimedia Networks ◽  
Useful Knowledge ◽  
Large Databases ◽  
Efficient Retrieval

Multimedia mining primarily involves information analysis and retrieval based on implicit knowledge. The ever increasing digital image databases on the internet has created a need for using multimedia mining on these databases for effective and efficient retrieval of images. Contents of an image can be expressed in different features such as Shape, Texture and Intensity-distribution (STI). Content Based Image Retrieval (CBIR) is the efficient retrieval of relevant images from large databases based on features extracted from the image. The emergence and proliferation of social network sites such as Facebook, Twitter and LinkedIn and other multimedia networks such as Flickr has further accelerated the need of efficient CBIR systems. Analyzing this huge amount of multimedia data to discover useful knowledge is a challenging task. Most of the existing systems either concentrate on a single representation of all features or linear combination of these features. The need of the day is New Image Mining techniques need to be explored and a self-adaptable CBIR system needs to be developed.

scholarly journals Image retrieval techniques: a survey

2017 ◽  
Vol 7 (1.2) ◽  
pp. 215 ◽  
Author(s):  
Aman Dureja ◽  
Payal Pahwa
Keyword(s):  
Image Retrieval ◽  
Medical Systems ◽  
Digital Repositories ◽  
Advantages And Disadvantages ◽  
Retrieval Systems ◽  
Large Databases ◽  
Base Method ◽  
Efficient Retrieval ◽  
Similar Images ◽  
Large Image Databases

In the recent years, the development in computer technologies and multimedia applications has led to the production of huge digital images and large image databases, and it is increasing rapidly. There are several different areas in which image retrieval plays a crucial role like Medical systems, Forensic Labs, Tourism Promotion, etc. Thus retrieval of similar images is a challenge. To tackle this rapid growth in digital repositories it is necessary to develop image retrieval systems, which can operate on large databases. There are basically three techniques, which is useful for efficient retrieval of images. With these techniques, the number of methods has been modified for the efficient image retrieval of images. In this paper, we presented the survey of different techniques that has been used starting from Image retrieval using visual features and latest by the deep learning with CNN that contains the number of layers and now becomes the best base method for retrieval of images from the large databases. In the last section, we have made the analysis between various developed techniques and showed the advantages and disadvantages of various techniques.

Data Mining-Based CBIR System

2016 ◽  
pp. 244-261
Author(s):  
Shruti Kohli ◽  
Vijay Shankar Gupta
Keyword(s):  
Data Mining ◽  
Social Network Sites ◽  
Image Databases ◽  
Multimedia Data ◽  
Content Based Image Retrieval ◽  
The Internet ◽  
Multimedia Networks ◽  
Useful Knowledge ◽  
Large Databases ◽  
Efficient Retrieval

Multimedia mining primarily involves information analysis and retrieval based on implicit knowledge. The ever increasing digital image databases on the internet has created a need for using multimedia mining on these databases for effective and efficient retrieval of images. Contents of an image can be expressed in different features such as Shape, Texture and Intensity-distribution (STI). Content Based Image Retrieval (CBIR) is the efficient retrieval of relevant images from large databases based on features extracted from the image. The emergence and proliferation of social network sites such as Facebook, Twitter and LinkedIn and other multimedia networks such as Flickr has further accelerated the need of efficient CBIR systems. Analyzing this huge amount of multimedia data to discover useful knowledge is a challenging task. Most of the existing systems either concentrate on a single representation of all features or linear combination of these features. The need of the day is New Image Mining techniques need to be explored and a self-adaptable CBIR system needs to be developed.

Converging Evidence for Developmental Trauma Disorder: Empirical Support From Large Databases

2008 ◽  
Author(s):  
Bradley C. Stolbach ◽  
Frank Putnam ◽  
Melissa Perry ◽  
Karen Putnam ◽  
William Harris ◽  
...  
Keyword(s):  
Empirical Support ◽  
Developmental Trauma ◽  
Developmental Trauma Disorder ◽  
Large Databases

ClusPhylo: Spark Based Fast and Reliable Approach for Reconstruction of Phylogenetic Network Using Large Databases

2017 ◽  
Vol 6 (6) ◽  
Author(s):  
S. Malik ◽  
S. Khatri ◽  
D. Sharma
Keyword(s):  
Phylogenetic Network ◽  
Large Databases

The Use if GIS Tools in Tourism Research on the Example of Wodzislaw Poviat

2012 ◽  
Vol 1 (1) ◽  
pp. 51-56
Author(s):  
Katarzyna Pukowiec
Keyword(s):  
Land Development ◽  
Graphic Representation ◽  
Infrastructure Development ◽  
Tourism Research ◽  
Gis Tools ◽  
Large Databases ◽  
Tourist Infrastructure ◽  
Tourist Development ◽  
Gis Software

Abstract The activities in name of tourist development in Wodzislaw poviat are the reason to evaluate the tourist land development. The evaluation was prepared on the basis of selected indexes characterizing the level of tourist infrastructure development. It considered: the number of lodgings per km2, the number of restaurants per km2, the amount of additional attractions per km2 and the density of tourist tracks. This database was analyzed by the use of GIS tools. Using GIS software allowed working with large databases and provided the possibility to create a graphic representation of the results. The level of tourist land development is diversified and depends on it function. The cities with the best developed tourist infrastructure are Wodzislaw Slaski, Radlin, Pszow, Rydultowy and town in Odra Valley: Olza, Bukow and Nieboczowy. Pszow, Gorzyce and Godow commons have the biggest density of tourist tracks.

Efficient Retrieval of Relevant Documents by Constructing Ontology Framework

2019 ◽  
Vol 7 (5) ◽  
pp. 1737-1740
Author(s):  
Sharvali S. Sarnaik ◽  
Ajit S. Patil
Keyword(s):  
Efficient Retrieval

Study on audit data acquisition methods oriented to large databases

2008 ◽  
Vol 28 (8) ◽  
pp. 2144-2146
Author(s):  
Wei CHEN
Keyword(s):  
Data Acquisition ◽  
Audit Data ◽  
Large Databases
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