Preprints

Filtering by Subject: Software Engineering

A Serious Gaming Framework for Decision Support on Hydrological Hazards

Yusuf Sermet, Ibrahim Demir, Marian Muste

Published: 2020-03-17
Subjects: Civil and Environmental Engineering, Computer Sciences, Databases and Information Systems, Engineering, Environmental Education, Environmental Engineering, Environmental Sciences, Physical Sciences and Mathematics, Software Engineering, Sustainability, Water Resource Management

In this study, a web-based decision support tool (DST) was developed for hydrological multi-hazard analysis while employing gamification techniques to introduce a competitive element. The serious gaming environment provides functionalities for intuitive management, visualization, and analysis of geospatial, hydrological, and economic data to help stakeholders in the decision-making process [...]

Digital photogrammetry of historical aerial photographs using open-source software

Jose Ramon Martinez Batlle

Published: 2018-07-06
Subjects: Computer Sciences, Earth Sciences, Geomorphology, Physical Sciences and Mathematics, Programming Languages and Compilers, Software Engineering

Several collections of aerial photographs have been acquired in the Dominican Republic during the last 70 years. Although many of these sources are increasingly becoming available as scanned images, limited digital photogrammetric processing has been done, mainly because of the unaffordable prices of proprietary software licenses and the lack of clear workflows for processing historical photos. [...]

Fish species classification in underwater video monitoring using Convolutional Neural Networks

Frederik Kratzert, Helmut Mader

Published: 2018-05-15
Subjects: Animal Sciences, Aquaculture and Fisheries Life Sciences, Computer Sciences, Environmental Monitoring, Environmental Sciences, Life Sciences, Other Life Sciences, Physical Sciences and Mathematics, Software Engineering

This report presents a case study for automatic fish species classification in underwater video monitoring of fish passes. Although the presented approach is based on the FishCam monitoring system, it can be used with any video-based monitoring system. The presented classification scheme in this study, is based on Convolutional Neural Networks that do not require the calculation of any [...]

  • 1 
search

You can search by:

  • Title
  • Keywords
  • Author Name
  • Author Affiliation