Patrick Mäder

机构: Prof. Dr.-Ing. of Computer Science, Technische Universität Ilmenau | iDiv | FSU Jena

主页: tu-ilmenau.de

每年引用次数

引用次数

引用: 6,055

H-指数: 41

I10-指数 : 99

出版物: 209

标题

引用次数

年份

A visual traceability modeling language

Jane Cleland-Huang , Patrick Mäder
model driven engineering languages and systems 226 -240

2010

Aufrechterhaltung von Traceability Links während evolutionärer Softwareentwicklung.

Ilka Philippow , Patrick Mäder , Matthias Riebisch
Softwaretechnik-trends 26

2006

Traceability Gap Analysis for Assessing the Conformance of Software Traceability to Relevant Guidelines.

Tobias Kuschke , Jane Cleland-Huang , Patrick Mäder , Patrick Rempel
Software Engineering & Management 120 -121

2015

Flora Incognita – Halbautomatische Bestimmung der Pflanzenarten Thüringens mit dem Smartphone

Angelika Thuille , Marco Seeland , Patrick Mäder , Jana Wäldchen
Landschaftspflege und Naturschutz in Thüringen 53 ( 3) 121 -125

2016

Do developers benefit from requirements traceability when evolving and maintaining a software system

Patrick Mäder , Alexander Egyed
Software Engineering 109 -110

2016

Are Graph Query Languages Applicable for Requirements Traceability Analysis

Patrick Mäder , Christoph Borowski , David Akehurst , Michael Rath
REFSQ Workshops

2017

Live Study Proposal: Collecting Natural Language Trace Queries.

Jane Cleland-Huang , Alexander Rasin , Sugandha Lohar , Patrick Mäder
REFSQ Workshops 207 -210

2015

Integrating context-based recommendation with deep NN image classification for plant identification tasks

Patrick Mäder , David Boho , Wittich, Hans, Christian
ICEI 2018 : 10th International Conference on Ecological Informatics- Translating Ecological Data into Knowledge and Decisions in a Rapidly Changing World. 24-28 September, 2018. Jena, Germany

2018

Multi-view classification with convolutional neural networks.

Marco Seeland , Patrick Mäder
PLOS ONE 16 ( 1)

2021

OmniDet: Surround View Cameras based Multi-task Visual Perception Network for Autonomous Driving

Patrick Mäder , Senthil Yogamani , Isabelle Leang , Stefan Milz
arXiv: Computer Vision and Pattern Recognition

2021

The Flora Incognita app – Interactive plant species identification

Marco Seeland , Patrick Mäder , Jana Wäldchen , Michael Rzanny
Methods in Ecology and Evolution

2021

Defocus particle tracking: A comparison of methods based on model functions, cross-correlation, and neural networks

Rune Barnkob , Christian Cierpka , Patrick Mäder , Massimiliano Rossi
Measurement Science and Technology

2021

Crowd‐sourced plant occurrence data provide a reliable description of macroecological gradients

Marco Seeland , Patrick Mäder , Jana Wäldchen , Miguel D. Mahecha
Ecography

2021

Can method data dependencies support the assessment of traceability between requirements and source code

Hongyu Kuang , Patrick Mäder , Hao Hu , Achraf Ghabi
Journal of Software: Evolution and Process 27 ( 11) 838 -866

2015

A definition-by-example approach and visual language for activity patterns in engineering disciplines.

Mario Janke , Tobias Kuschke , Patrick Mäder
PLOS ONE 15 ( 1)

2020

On the use of a cascaded convolutional neural network for three-dimensional flow measurements using astigmatic PTV

Jörg König , Minqian Chen , Wiebke Rösing , David Boho
Measurement Science and Technology 31 ( 7) 074015

2020

Request for comments: conversation patterns in issue tracking systems of open-source projects

Michael Rath , Patrick Mäder
acm symposium on applied computing 1414 -1417

2020

Plant species classification using flower images-A comparative study of local feature representations.

Marco Seeland , Michael Rzanny , Nedal Alaqraa , Jana Wäldchen
PLOS ONE 12 ( 2) 1 -29

2017

Variability points and design pattern usage in architectural tactics

Mehdi Mirakhorli , Patrick Mäder , Jane Cleland-Huang
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering - FSE '12 52

2012

Efficiently Annotating Object Images with Absolute Size Information Using Mobile Devices

Martin Hofmann , Marco Seeland , Patrick Mäder
International Journal of Computer Vision 127 ( 2) 207 -224

2019