Teo Susnjak
Teo Susnjak
Lecturer of Information Technology, Massey University Albany, New Zealand
Verified email at massey.ac.nz
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
Influences on regression testing strategies in agile software development environments
D Parsons, T Susnjak, M Lange
Software Quality Journal, 1-23, 2013
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, 2017
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 Electricalá…, 2018
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
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
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
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
Int. J. Knowl. Eng 3 (2), 43-47, 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
Coderetreats: Reflective practice and the game of life
D Parsons, A Mathrani, T Susnjak, A Leist
IEEE software 31 (4), 58-64, 2014
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
The Application of Machine Learning Techniques for Predicting Results in Team Sport: A Review
R Bunker, T Susnjak
arXiv preprint arXiv:1912.11762, 2019
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, 2019
Study of a copper capacitive MEMS as a sensor for automotive fuel evaluation
LGD Mendonša, B Barazani, BB Chaves, D Torikai, RC Ibrahim, ...
Proc. ABCM Symp. Ser. Mechatron. 5, 1400-1408, 2012
A reconfigurable hybrid intelligent system for robot navigation
NH Reyes, ALC Barczak, T Susnjak
Massey University, 2011
A new ensemble-based cascaded framework for multiclass training with simple weak learners
T Susnjak, A Barczak, N Reyes, K Hawick
Computer Analysis of Images and Patterns, 563-570, 2011
Adaptive ensemble based learning in non-stationary environments with variable concept drift
T Susnjak, A Barczak, K Hawick
Neural Information Processing. Theory and Algorithms, 438-445, 2010
A modular approach to training cascades of boosted ensembles
T Susnjak, A Barczak, K Hawick
Structural, syntactic, and statistical pattern recognition, 640-649, 2010
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
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