Teo Susnjak
Teo Susnjak
Senior Lecturer in Computer Science and Information Technology, Massey University, New Zealand
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Cited by
Cited by
A new 2D static hand gesture colour image dataset for asl gestures
ALC Barczak, NH Reyes, M Abastillas, A Piccio, T Susnjak
Res Lett Inf Math Sci 15, 12-20, 2011
On predicting academic performance with process mining in learning analytics
R Umer, T Susnjak, A Mathrani, S Suriadi
Journal of Research in Innovative Teaching & Learning 10 (2), 160-176, 2017
The inadequacy of entropy-based ransomware detection
T McIntosh, J Jang-Jaccard, P Watters, T Susnjak
International conference on neural information processing, 181-189, 2019
Influences on regression testing strategies in agile software development environments
D Parsons, T Susnjak, M Lange
Software Quality Journal, 1-23, 2013
Using educational data mining techniques to increase the prediction accuracy of student academic performance
G Ramaswami, T Susnjak, A Mathrani, J Lim, P Garcia
Information and Learning Sciences 120 (7/8), 451-467, 2019
A comprehensive performance analysis of Apache Hadoop and Apache Spark for large scale data sets using HiBench
N Ahmed, ALC Barczak, T Susnjak, MA Rashid
Journal of Big Data 7 (1), 1-18, 2020
A learning analytics approach: Using online weekly student engagement data to make predictions on student performance
R Umer, T Susnjak, A Mathrani, S Suriadi
2018 International conference on computing, electronic and electrical …, 2018
A systematic literature review: What is the current stance towards weight stigmatization in social media platforms?
VU Wanniarachchi, A Mathrani, T Susnjak, C Scogings
International Journal of Human-Computer Studies 135, 102371, 2020
The application of machine learning techniques for predicting results in team sport: a review
R Bunker, T Susnjak
arXiv preprint arXiv:1912.11762, 2019
Analysis of feature invariance and discrimination for hand images: Fourier descriptors versus moment invariants
ALC Barczak, A Gilman, NH Reyes, T Susnjak
International conference image and vision computing New Zealand IVCNZ2011, 2011
Mining activity log data to predict student's outcome in a course
R Umer, A Mathrani, T Susnjak, S Lim
proceedings of the 2019 international conference on big data and education …, 2019
Adaptive cascade of boosted ensembles for face detection in concept drift
T Susnjak, ALC Barczak, KA Hawick
Neural Computing & Applications 21 (4), 671-682, 2012
A decomposition machine-learning strategy for automated fruit grading
T Susnjak, A Barczak, N Reyes
Proceedings of the World Congress on Engineering and Computer Science 2, 2013
Accelerating classifier training using AdaBoost within cascades of boosted ensembles
T Susnjak
Science in Computer Sciences, Massey University, Auckland, New Zealand, 2009
Prediction of students’ dropout in MOOC environment
R Umer, T Susnjak, A Mathrani, S Suriadi
International Journal of Knowledge Engineering 3 (2), 43-47, 2017
Using data-driven and process mining techniques for identifying and characterizing problem gamblers in New Zealand
S Suriadi, T Susnjak, A Ponder-Sutton, P Watters, CR Schumacher
RTU Press, 2016
Coderetreats: Reflective practice and the game of life
D Parsons, A Mathrani, T Susnjak, A Leist
IEEE software 31 (4), 58-64, 2014
Fast and smooth replanning for navigation in partially unknown terrain: the hybrid fuzzy-D* lite algorithm
NH Reyes, ALC Barczak, T Susnjak, A Jordan
Robot Intelligence Technology and Applications 4, 31-41, 2017
Design from detail: Analyzing data from a global day of coderetreat
D Parsons, T Susnjak, A Mathrani
Information and Software Technology 75, 39-55, 2016
A parallelization model for performance characterization of Spark Big Data jobs on Hadoop clusters
N Ahmed, ALC Barczak, MA Rashid, T Susnjak
Journal of Big Data 8 (1), 1-28, 2021
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