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Brendon J. Woodford
Person information
- affiliation: University of Otago, Dunedin, New Zealand
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2020 – today
- 2024
- [j6]Ahmad Ghandour
, Brendon J. Woodford
Ethical Considerations in the Use of ChatGPT: An Exploration Through the Lens of Five Moral Dimensions. IEEE Access 12: 60682-60693 (2024) - [j5]Ahmad Ghandour, Brendon J. Woodford, Hesham Abusaimeh:
Corrections to "Ethical Considerations in the Use of ChatGPT: An Exploration Through the Lens of Five Moral Dimensions". IEEE Access 12: 162509 (2024) - 2023
- [c28]Ahmad Ghandour
Guidelines to Develop AI Ethics Policy in Organizations: Perspectives Informed from Two Different Countries' Laws. ACIT 2023: 1-9 - [c27]Fathima Nuzla Ismail
A Comparison of One-Class Versus Two-Class Machine Learning Models for Wildfire Prediction in California. AusDM 2023: 239-253 - [c26]Brendon J. Woodford:
Automatic Parameter Optimisation Framework for ECoS-based Models. IJCNN 2023: 1-8 - 2022
- [c25]Ahmad Ghandour
Means to Support the Ends: Forums that Escape the Official Gaze in the Educational Institutions. ACIT 2022: 1-5 - [c24]Brendon J. Woodford
Boosted Self-evolving Neural Networks for Pattern Recognition. AI 2022: 456-469 - 2021
- [e1]Nigel Stanger
ACSW '21: 2021 Australasian Computer Science Week Multiconference, Dunedin, New Zealand, 1-5 February, 2021. ACM 2021, ISBN 978-1-4503-8956-3 [contents] - 2020
- [c23]Ahmad Ghandour
COVID-19 Impact on E-Commerce in UAE. ACIT 2020: 1-8 - [c22]Brendon J. Woodford, Ahmad Ghandour
An Information Retrieval-Based Approach to Activity Recognition in Smart Homes. ICSOC Workshops 2020: 583-595
2010 – 2019
- 2019
- [c21]Ahmad Ghandour
Ethical Issues in Artificial Intelligence in UAE. ACIT 2019: 262-266 - [c20]Fathima Nuzla Ismail
Evaluating the Boundaries of Big Data Environments for Machine Learning. Australasian Conference on Artificial Intelligence 2019: 253-264 - 2017
- [c19]Ahmad Shahi, Jeremiah D. Deng
Online Hidden Conditional Random Fields to Recognize Activity-Driven Behavior Using Adaptive Resilient Gradient Learning. ICONIP (1) 2017: 515-525 - [c18]Ahmad Shahi, Jeremiah D. Deng
A streaming ensemble classifier with multi-class imbalance learning for activity recognition. IJCNN 2017: 3983-3990 - [c17]Ahmad Shahi, Brendon J. Woodford, Hanhe Lin
Dynamic Real-Time Segmentation and Recognition of Activities Using a Multi-feature Windowing Approach. PAKDD (Workshops) 2017: 26-38 - 2016
- [c16]Hanhe Lin
Online Weighted Clustering for Real-time Abnormal Event Detection in Video Surveillance. ACM Multimedia 2016: 536-540 - [c15]Hanhe Lin
Shot Boundary Detection Using Multi-instance Incremental and Decremental One-Class Support Vector Machine. PAKDD (1) 2016: 165-176 - 2015
- [j4]Munir Shah
A Self-adaptive CodeBook (SACB) model for real-time background subtraction. Image Vis. Comput. 38: 52-64 (2015) - [c14]Ahmad Shahi, Brendon J. Woodford, Jeremiah D. Deng
Event Classification Using Adaptive Cluster-Based Ensemble Learning of Streaming Sensor Data. Australasian Conference on Artificial Intelligence 2015: 505-516 - [c13]Hanhe Lin
Anomaly detection in crowd scenes via online adaptive one-class support vector machines. ICIP 2015: 2434-2438 - 2014
- [j3]Munir Shah
Video background modeling: recent approaches, issues and our proposed techniques. Mach. Vis. Appl. 25(5): 1105-1119 (2014) - [c12]Hanhe Lin
Spatial-Temporal Pyramid Matching for Crowd Scene Analysis. MLSDA@PRICAI 2014: 12 - 2013
- [c11]Hanhe Lin
Event Detection Using Quantized Binary Code and Spatial-Temporal Locality Preserving Projections. Australasian Conference on Artificial Intelligence 2013: 123-134 - [c10]Munir Shah
Growing Neural Gas Video Background Model (GNG-BM). Australasian Conference on Artificial Intelligence 2013: 135-147 - [c9]Munir Shah
Improving Mixture of Gaussians background model through adaptive learning and Spatio-Temporal voting. ICIP 2013: 3436-3440 - 2012
- [c8]Munir Shah
Illumination Invariant Background Model Using Mixture of Gaussians and SURF Features. ACCV Workshops (1) 2012: 308-314 - [c7]Munir Shah
Enhancing the mixture of Gaussians background model with local matching and local adaptive learning. IVCNZ 2012: 103-108 - [c6]Hanhe Lin
Video manifold modelling: finding the right parameter settings for anomaly detection. IVCNZ 2012: 168-173 - 2011
- [c5]Munir Shah
Enhanced Codebook Model for Real-Time Background Subtraction. ICONIP (3) 2011: 449-458 - 2010
- [c4]Brendon J. Woodford:
Automatic optimization of pruning in evolving fuzzy neural networks using an entropy measure. IJCNN 2010: 1-7
2000 – 2009
- 2008
- [j2]Brendon J. Woodford:
Evolving neurocomputing systems for horticulture applications. Appl. Soft Comput. 8(1): 564-578 (2008) - 2004
- [c3]Brendon J. Woodford, Da Deng, George L. Benwell:
A wavelet-based neuro-fuzzy system for data mining small image sets. ACSW 2004: 139-143 - 2001
- [c2]Brendon J. Woodford, Nikola K. Kasabov:
Ensembles of EFuNNs: An Architecture for a Mutlimodule Classifier. FUZZ-IEEE 2001: 1573-1576 - 2000
- [j1]Nikola K. Kasabov, Steven A. Israel, Brendon J. Woodford:
The Application of Hybrid Evolving Connectionist Systems to Image Classification. J. Adv. Comput. Intell. Intell. Informatics 4(1): 57-65 (2000)
1990 – 1999
- 1999
- [c1]Brendon J. Woodford:
Analysing Images of Pest Damage to Apples using Wavelets. New Zealand Computer Science Research Students' Conference 1999: 101-108
Coauthor Index
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