scholarly journals Planning for OBIS: Examining Relationships with Existing National and International Biodiversity Information Systems

Oceanography ◽  
2000 ◽  
Vol 13 (3) ◽  
pp. 31-38 ◽  
Author(s):  
Fornwall
Keyword(s):  
Information Systems ◽  
Biodiversity Information

scholarly journals A digital library framework for biodiversity information systems

2006 ◽  
Vol 6 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Ricardo da S. Torres ◽  
Claudia Bauzer Medeiros ◽  
Marcos André Gonçcalves ◽  
Edward A. Fox
Keyword(s):  
Information Systems ◽  
Digital Library ◽  
Biodiversity Information

scholarly journals Model Framework for Development of Biodiversity Information Systems

2019 ◽  
Vol 1230 ◽  
pp. 012012
Author(s):  
Edy Budiman ◽  
Novianti Puspitasari ◽  
Masna Wati ◽  
Haviluddin ◽  
Robbi Rahim
Keyword(s):  
Information Systems ◽  
Model Framework ◽  
Biodiversity Information

scholarly journals FDEIR: Content-Based Image Retrieval using Fast Demeanor Ensemble Features

2021 ◽  
Vol 12 (2) ◽  
pp. 1660-1671
Author(s):  
Punit Soni, Et. al.
Keyword(s):  
Information Systems ◽  
Image Retrieval ◽  
Digital Libraries ◽  
Content Based Image Retrieval ◽  
Digital Information ◽  
Automated Systems ◽  
System Complexity ◽  
Day By Day ◽  
Biodiversity Information ◽  
Selection Phase

The demand for CBIR-based systems is increasing day-by-day with the increase of its applications. Nowadays, various digital information systems like Medicine, Digital Libraries, Biodiversity information systems, Fingerprint Identification, crime prevention, and many more are in trend, and all these systems need accuracy. Several Automated Systems were earlier developed using features to improve the systems' accuracy, but it introduces complexity and speed. A fast Demeanor Ensemble features-based approach is proposed to cope with this issue, which also deals with accuracy, speeds up the system, and reduces its complexity. Different shape-based features are used to form 3-set composite features, followed by the selection phase where the ALO algorithm is utilized and reduces system complexity. The accuracy of the proposed system is estimated using distance-based matching methods. Correl-1000 dataset is used to analyze the system's performance based on different metrics, and the results show the proposed system's ability.

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