scholarly journals FAST TEMPLATE MATCHING FOR MEASURING VISIT FREQUENCIES OF DYNAMIC WEB ADVERTISEMENTS

2008 ◽  
Keyword(s):  
Template Matching ◽  
Dynamic Web

Ensemble Visual Content based Search and Retrieval for Natural Scene Images

2019 ◽  
Vol 12 ◽  
Author(s):  
Pushpendra Singh ◽  
P.N. Hrisheekesha ◽  
Vinai Kumar Singh
Keyword(s):  
Template Matching ◽  
Feature Descriptor ◽  
Natural Scene ◽  
Visual Content ◽  
Other Information ◽  
Similar Images ◽  
State Of Art ◽  
Natural Scene Images ◽  
Hybrid Methodology ◽  
Search And Retrieval

Content based image retrieval (CBIR) is one of the field for information retrieval where similar images are retrieved from database based on the various image descriptive parameters. The image descriptor vector is used by machine learning based systems to store, learn and template matching. These feature descriptor vectors locally or globally demonstrate the visual content present in an image using texture, color, shape, and other information. In past, several algorithms were proposed to fetch the variety of contents from an image based on which the image is retrieved from database. But, the literature suggests that the precision and recall for the gained results using single content descriptor is not significant. The main vision of this paper is to categorize and evaluate those algorithms, which were proposed in the interval of last 10 years. In addition, experiment is performed using a hybrid content descriptors methodology that helps to gain the significant results as compared with state-of-art algorithms. The hybrid methodology decreases the error rate and improves the precision and recall for large natural scene images dataset having more than 20 classes.

Cognition System of Bolt Hole Using Template Matching

2011 ◽  
Author(s):  
Gwan Ryong Baek ◽  
Yung Hak Mo ◽  
Jae Sik Jeong ◽  
Jung Min Park ◽  
Myo Taeg Lim
Keyword(s):  
Template Matching

scholarly journals Evaluating the Performance of Three Popular Web Mapping Libraries: A Case Study Using Argentina’s Life Quality Index

2020 ◽  
Vol 9 (10) ◽  
pp. 563
Author(s):  
Alejandro Zunino ◽  
Guillermo Velázquez ◽  
Juan Pablo Celemín ◽  
Cristian Mateos ◽  
Matías Hirsch ◽  
...  
Keyword(s):  
Life Quality ◽  
Web Technologies ◽  
Web Mapping ◽  
Network Bandwidth ◽  
Web Map ◽  
Raster Maps ◽  
Dynamic Web ◽  
Network Usage ◽  
Overall Performance

Recent Web technologies such as HTML5, JavaScript, and WebGL have enabled powerful and highly dynamic Web mapping applications executing on standard Web browsers. Despite the complexity for developing such applications has been greatly reduced by Web mapping libraries, developers face many choices to achieve optimal performance and network usage. This scenario is even more complex when considering different representations of geographical data (raster, raw data or vector) and variety of devices (tablets, smartphones, and personal computers). This paper compares the performance and network usage of three popular JavaScript Web mapping libraries for implementing a Web map using different representations for geodata, and executing on different devices. In the experiments, Mapbox GL JS achieved the best overall performance on mid and high end devices for displaying raster or vector maps, while OpenLayers was the best for raster maps on all devices. Vector-based maps are a safe bet for new Web maps, since performance is on par with raster maps on mid-end smartphones, with significant less network bandwidth requirements.

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