scholarly journals GEO-TAGGED IMAGE RETRIEVAL FROM MAPILLARY STREET IMAGES FOR A TARGET BUILDING

2020 ◽  
Vol XLIV-4/W3-2020 ◽  
pp. 151-158
Author(s):  
N. Çelik ◽  
E. Sümer
Keyword(s):  
Image Retrieval ◽  
Web Application ◽  
Selection Process ◽  
Partial Coverage

Abstract. This study aims to investigate the possibility to automate the image selection process for the target building from Mapillary images through a web application where the user only initiates one image of the target building as a query. Using the data provided with Mapillary API and Overpass API, all images having full or partial coverage of the target building were selected. Then the images were segmented by using a pre-trained U-Net model to discard any images having less than 20% building coverage. The experiments showed promising results yielding 0.971 and 0.887 of overall accuracy after segmentation steps for two different target buildings.

The role of developers’ social relationships in improving service selection

2016 ◽  
Vol 12 (4) ◽  
pp. 477-503 ◽  
Author(s):  
Devis Bianchini ◽  
Valeria De Antonellis ◽  
Michele Melchiori
Keyword(s):  
Social Network ◽  
Social Relationships ◽  
Web Application ◽  
Selection Process ◽  
Service Selection ◽  
Third Party ◽  
Data Service ◽  
Application Development ◽  
Content Type ◽  
Data Services

Purpose Modern Enterprise Web Application development can exploit third-party software components, both internal and external to the enterprise, that provide access to huge and valuable data sets, tested by millions of users and often available as Web application programming interfaces (APIs). In this context, the developers have to select the right data services and might rely, to this purpose, on advanced techniques, based on functional and non-functional data service descriptive features. This paper focuses on this selection task where data service selection may be difficult because the developer has no control on services, and source reputation could be only partially known. Design/methodology/approach The proposed framework and methodology are apt to provide advanced search and ranking techniques by considering: lightweight data service descriptions, in terms of (semantic) tags and technical aspects; previously developed aggregations of data services, to use in the selection process of a service the past experiences with the services when used in similar applications; social relationships between developers (social network) and their credibility evaluations. This paper also discusses some experimental results regarding the plan to expand other experiments to check how developers feel using the approach. Findings In this paper, a data service selection framework that extends and specializes an existing one for Web APIs selection is presented. The revised multi-layered model for data services is discussed and proper metrics relying on it, meant for supporting the selection of data services in a context of Web application design, are introduced. Model and metrics take into account the network of social relationships between developers, to exploit them for estimating the importance that a developer assigns to other developers’ experience. Originality/value This research, with respect to the state of the art, focuses attention on developers’ social networks in an enterprise context, integrating the developers’ credibility assessment and implementing the social network-based data service selection on top of a rich framework based on a multi-perspective model for data services.

scholarly journals Luigi: Large-scale histopathological image retrieval system using deep texture representations

2018 ◽  
Author(s):  
Daisuke Komura ◽  
Keisuke Fukuta ◽  
Ken Tominaga ◽  
Akihiro Kawabe ◽  
Hirotomo Koda ◽  
...  
Keyword(s):  
Image Retrieval ◽  
Web Application ◽  
Large Scale ◽  
Nearest Neighbor ◽  
Smartphone Application ◽  
Nearest Neighbor Search ◽  
The Cancer Genome Atlas ◽  
Image Feature ◽  
Query Image ◽  
Histopathological Images

AbstractBackgroundAs a large number of digital histopathological images have been accumulated, there is a growing demand of content-based image retrieval (CBIR) in pathology for educational, diagnostic, or research purposes. However, no CBIR systems in digital pathology are publicly available.ResultsWe developed a web application, the Luigi system, which retrieves similar histopathological images from various cancer cases. Using deep texture representations computed with a pre-trained convolutional neural network as an image feature in conjunction with an approximate nearest neighbor search method, the Luigi system provides fast and accurate results for any type of tissue or cell without the need for further training. In addition, users can easily submit query images of an appropriate scale into the Luigi system and view the retrieved results using our smartphone application. The cases stored in the Luigi database are obtained from The Cancer Genome Atlas with rich clinical, pathological, and molecular information. We tested the Luigi system by querying typical cancerous regions from four cancer types, and confirmed successful retrieval of relevant images.ConclusionsThe Luigi system will help students, pathologists, and researchers easily retrieve histopathological images of various cancers similar to those of the query image.

scholarly journals Modified Differential Evolution Algorithm for a Transportation Software Application

2019 ◽  
Vol 5 (4) ◽  
pp. 84
Author(s):  
Supattananon ◽  
Akararungruangkul
Keyword(s):  
Differential Evolution ◽  
Real Time ◽  
Web Application ◽  
Transportation Problem ◽  
Selection Process ◽  
Differential Evolution Algorithm ◽  
Optimal Solution ◽  
Raw Material ◽  
Production Plant ◽  
Solution Approach

This research developed a solution approach that is a combination of a web application and the modified differential evolution (MDE) algorithm, aimed at solving a real-time transportation problem. A case study involving an inbound transportation problem in a company that has to plan the direct shipping of a finished product to be collected at the depot where the vehicles are located is presented. In the newly designed transportation plan, a vehicle will go to pick up the raw material required by a certain production plant from the supplier to deliver to the production plant in a manner that aims to reduce the transportation costs for the whole system. The reoptimized routing is executed when new information is found. The information that is updated is obtained from the web application and the reoptimization process is executed using the MDE algorithm developed to provide the solution to the problem. Generally, the original DE comprises of four steps: (1) randomly building the initial set of the solution, (2) executing the mutation process, (3) executing the recombination process, and (4) executing the selection process. Originally, for the selection process in DE, the algorithm accepted only the better solution, but in this paper, four new selection formulas are presented that can accept a solution that is worse than the current best solution. The formula is used to increase the possibility of escaping from the local optimal solution. The computational results show that the MDE outperformed the original DE in all tested instances. The benefit of using real-time decision-making is that it can increase the company’s profit by 5.90% to 6.42%.

An Image Retrieval Model Combining Ontology and Probabilistic Ranking

2013 ◽  
pp. 61-73
Author(s):  
Lisa Fan ◽  
Botang Li
Keyword(s):  
World Wide Web ◽  
Knowledge Representation ◽  
Cognitive Load ◽  
Image Retrieval ◽  
Web Application ◽  
World Wide ◽  
Experimental Results ◽  
Retrieval Method ◽  
Multimedia Documents ◽  
Model Combining

The demand for image retrieval and browsing online is growing dramatically. There are hundreds of millions of images available on the current World Wide Web. For multimedia documents, the typical keyword-based retrieval methods assume that the user has an exact goal in mind in searching a set of images whereas users normally do not know what they want, or the user faces a repository of images whose domain is less known and content is semantically complicated. In these cases it is difficult to decide what keywords to use for the query. In this chapter, we propose a user-centered image retrieval method based on the current Web, keyword-based annotation structure, and combining ontology guided knowledge representation and probabilistic ranking. A Web application for image retrieval using the proposed approach has been implemented. The model provides a recommendation subsystem to support and assist the user modifying the queries and reducing the user’s cognitive load with the searching space. Experimental results show that the image retrieval recall and precision rates are increased and therefore demonstrate the effectiveness of the model.

A User-Driven Ontology Guided Image Retrieval Model

2011 ◽  
pp. 272-282
Author(s):  
Lisa Fan ◽  
Botang Li
Keyword(s):  
World Wide Web ◽  
Knowledge Representation ◽  
Cognitive Load ◽  
Image Retrieval ◽  
Web Application ◽  
World Wide ◽  
Experimental Results ◽  
Retrieval Method ◽  
Multimedia Documents ◽  
Specific Goal

The demand for image retrieval and browsing online is growing dramatically. There are hundreds of millions of images available on the current World Wide Web. For multimedia documents, the typical keyword-based retrieval methods assume that the user has a specific goal in mind by using accurate query keywords in searching a set of images. Whereas the users may face with a repository of images whose domain is less known and content is semantically complicated, or the users may only generally know what they search for. In these cases it is difficult to decide what exact keywords to use for the query. In this article, we propose a user-centered image retrieval method that is based on the current Web, keyword-based annotation structure, and combining Ontology guided knowledge representation and probabilistic ranking. A prototype of web application for image retrieval using the proposed approach has been implemented. The model provides a recommendation subsystem to support and assist the user modifying the queries and reduces the user’s cognitive load with the searching space. Experimental results show that the image retrieval recall and precision rates increased and therefore demonstrates the effectiveness of the model.

A comparison of the United Kingdom Clinical Aptitude Test (UK-CAT) with a traditional admission selection process

2009 ◽  
pp. 1-6 ◽  
Author(s):  
Nishan Fernando ◽  
Gordon Prescott ◽  
Jennifer Cleland ◽  
Kathryn Greaves ◽  
Hamish McKenzie
Keyword(s):  
United Kingdom ◽  
Selection Process ◽  
Aptitude Test ◽  
The United Kingdom

Two Short Tests Fail to Detect Vigilance Decrements

2001 ◽  
Vol 17 (1) ◽  
pp. 48-55 ◽  
Author(s):  
Juan Botella ◽  
María José Contreras ◽  
Pei-Chun Shih ◽  
Víctor Rubio
Keyword(s):  
Individual Differences ◽  
High Performance ◽  
Selection Process ◽  
Vigilance Task ◽  
Air Traffic Controllers ◽  
Job Selection ◽  
Performance Deterioration ◽  
Short Test ◽  
Psychological Dimensions

Summary: Deterioration in performance associated with decreased ability to sustain attention may be found in long and tedious task sessions. The necessity for assessing a number of psychological dimensions in a single session often demands “short” tests capable of assessing individual differences in abilities such as vigilance and maintenance of high performance levels. In the present paper two tasks were selected as candidates for playing this role, the Abbreviated Vigilance Task (AVT) by Temple, Warm, Dember, LaGrange and Matthews (1996) and the Continuous Attention Test (CAT) by Tiplady (1992) . However, when applied to a sample of 829 candidates in a job-selection process for air-traffic controllers, neither of them showed discriminative capacity. In a second study, an extended version of the CAT was applied to a similar sample of 667 subjects, but also proved incapable of properly detecting individual differences. In short, at least in a selection context such as that studied here, neither of the tasks appeared appropriate for playing the role of a “short” test for discriminating individual differences in performance deterioration in sustained attention.

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