Now showing items 1-4 of 4
Development of neural network based rules for confusion set disambiguation in LanguageTool
SKILL 2018 - Studierendenkonferenz Informatik
Confusion set disambiguation is a typical task for grammar checkers like LanguageTool. In this paper we present a neural network based approach which has low memory requirements, high precision with decent recall, and can easily be integrated into LanguageTool. Furthermore, adding support for new confusion pairs does not ...
Predicting How to Test Requirements: An Automated Approach
Software Engineering 2020
An important task in requirements engineering is to identify and determine how to verify a requirement (eg., by manual review, testing, or simulation; also called \emphpotential verification method). This information is required to effectively create test cases and verification plans for requirements. In this paper, ...
The Impact of Domain Knowledge on Applying Machine Learning Methods to Exoplanet Detection
Exoplanets do not emit electromagnetic waves which makes it challenging to detect them. Based on transit photometry, we trained a neural network on NASA Kepler space telescope data to detect exoplanets based on light intensity curves. We showcase, that with a well designed data pipeline, a small neural network is sufficient ...
From Physical to Virtual: Leveraging Drone Imagery to Automate Photovoltaic System Maintenance
Optimizing the maintenance of large-scale infrastructure can be a significant cost driver for small and medium-sized enterprises (SMEs). This paper presents a feasible approach to combine data from real-world physical structures collected through an automated maintenance process with cloud-based AI services to generate ...