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End-User Development for Artificial Intelligence: A Systematic Literature Review
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End-User Development for Artificial Intelligence: A Systematic Literature Review

Andrea Esposito
Miriana Calvano
Antonio Curci
Giuseppe Desolda
Rosa Lanzilotti
Claudia Lorusso
Antonio Piccinno
ArXiv (abs)PDFHTML

Papers citing "End-User Development for Artificial Intelligence: A Systematic Literature Review"

4 / 4 papers shown
Title
Machine Learning Operations (MLOps): Overview, Definition, and Architecture
Machine Learning Operations (MLOps): Overview, Definition, and Architecture
Dominik Kreuzberger
Niklas Kühl
Sebastian Hirschl
VLMAI4CE
59
351
0
04 May 2022
ML-Quadrat & DriotData: A Model-Driven Engineering Tool and a Low-Code Platform for Smart IoT Services
ML-Quadrat & DriotData: A Model-Driven Engineering Tool and a Low-Code Platform for Smart IoT Services
Armin Moin
Andrei Mituca
Moharram Challenger
A. Badii
Stephan Günnemann
20
4
0
06 Jul 2021
Trinity: A No-Code AI platform for complex spatial datasets
Trinity: A No-Code AI platform for complex spatial datasets
C. V. K. Iyer
Feili Hou
Henry Wang
Yonghong Wang
Kay Oh
Swetava Ganguli
Vipul Pandey
SyDa
63
23
0
21 Jun 2021
How Robust are Model Rankings: A Leaderboard Customization Approach for Equitable Evaluation
How Robust are Model Rankings: A Leaderboard Customization Approach for Equitable Evaluation
Swaroop Mishra
Anjana Arunkumar
65
26
0
10 Jun 2021

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