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ORCIDJeremiah D. Deng
Jeremiah Da Deng – Da Deng 0001
Person information
- affiliation: University of Otago
- affiliation: South China University of Technology
- affiliation: University of Hong Kong
Other persons with the same name
- Da Deng — disambiguation page
- Da Deng 0002 — Fudan University
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2020 – today
- 2023
[i11]Yuan Yue, Jeremiah D. Deng, Dirk De Ridder, Patrick Manning, Divya Adhia:
Variational Autoencoder Learns Better Feature Representations for EEG-based Obesity Classification. CoRR abs/2302.00789 (2023)- [i10]Jean Li, Dirk De Ridder, Divya Adhia, Matthew Hall, Jeremiah D. Deng:
Chronic pain detection from resting-state raw EEG signals using improved feature selection. CoRR abs/2306.15194 (2023) - 2022
- [j26]Alina Tetereva
, Jean Li, Jeremiah D. Deng, Argyris K. Stringaris, Narun Pat:
Capturing brain-cognition relationship: Integrating task-based fMRI across tasks markedly boosts prediction and test-retest reliability. NeuroImage 263: 119588 (2022) - [j25]Jinyong Hou, Xuejie Ding, Jeremiah D. Deng, Stephen Cranefield:
Deep adversarial transition learning using cross-grafted generative stacks. Neural Networks 149: 172-183 (2022) - [c59]Ying Pang, Haibo Zhang, Jeremiah D. Deng, Lizhi Peng, Fei Teng:
Rule-Based Collaborative Learning with Heterogeneous Local Learning Models. PAKDD (1) 2022: 639-651 - [c58]Jinyong Hou, Xuejie Ding, Jeremiah D. Deng:
Semi-Supervised Semantic Segmentation of Vessel Images using Leaking Perturbations. WACV 2022: 1769-1778 - [i9]Jinyong Hou, Jeremiah D. Deng, Stephen Cranefield, Xuejie Ding:
Variational Transfer Learning using Cross-Domain Latent Modulation. CoRR abs/2205.15523 (2022) - [i8]Yuan Yue, Dirk De Ridder, Patrick Manning, Samantha Ross, Jeremiah D. Deng:
Finding neural signatures for obesity using source-localized EEG features. CoRR abs/2208.14007 (2022) - [i7]Jeremiah D. Deng:
Sizing up the Batteries: Modelling of Energy-Harvesting Sensor Nodes in a Delay Tolerant Network. CoRR abs/2210.05316 (2022) - 2021
- [j24]Xiao-Min Hu, Shou-Rong Zhang, Min Li, Jeremiah D. Deng:
Multimodal particle swarm optimization for feature selection. Appl. Soft Comput. 113(Part): 107887 (2021) - [j23]Feng-Feng Wei, Wei-Neng Chen, Qiang Yang, Jeremiah D. Deng, Xiaonan Luo, Hu Jin, Jun Zhang:
A Classifier-Assisted Level-Based Learning Swarm Optimizer for Expensive Optimization. IEEE Trans. Evol. Comput. 25(2): 219-233 (2021) - [c57]Jinyong Hou, Jeremiah D. Deng, Stephen Cranefield, Xuejie Ding:
Cross-Domain Latent Modulation for Variational Transfer Learning. WACV 2021: 3148-3157 - [i6]Jinyong Hou, Xuejie Ding, Jeremiah D. Deng:
Semi-Supervised Semantic Segmentation of Vessel Images using Leaking Perturbations. CoRR abs/2110.11998 (2021) - 2020
- [j22]Hanhe Lin, Jeremiah D. Deng, Deike Albers, Felix Wilhelm Siebert:
Helmet Use Detection of Tracked Motorcycles Using CNN-Based Multi-Task Learning. IEEE Access 8: 162073-162084 (2020) - [j21]Xianbin Gu, Jeremiah D. Deng:
A multi-feature bipartite graph ensemble for image segmentation. Pattern Recognit. Lett. 131: 98-104 (2020) - [c56]Jean Li, Jeremiah D. Deng, Dirk De Ridder, Divya Adhia:
Gender Classification of EEG Signals using a Motif Attribute Classification Ensemble. IJCNN 2020: 1-8 - [i5]Jinyong Hou, Xuejie Ding, Stephen Cranefield, Jeremiah D. Deng:
Deep Adversarial Transition Learning using Cross-Grafted Generative Stacks. CoRR abs/2009.12028 (2020) - [i4]Jean Li, Jeremiah D. Deng, Divya Adhia, Dirk De Ridder:
Resting-state EEG sex classification using selected brain connectivity representation. CoRR abs/2012.11105 (2020) - [i3]Jinyong Hou, Jeremiah D. Deng, Stephen Cranefield, Xuejie Ding:
Cross-Domain Latent Modulation for Variational Transfer Learning. CoRR abs/2012.11727 (2020)
2010 – 2019
- 2019
- [j20]Sophie Zareei, Jeremiah D. Deng:
Energy harvesting modelling for self-powered fitness gadgets: a feasibility study. Int. J. Parallel Emergent Distributed Syst. 34(4): 412-429 (2019) - [c55]Jeremiah D. Deng:
Performance Modelling of Synchronized Predictive Sensing for Clustered Wireless Sensor Networks. APCC 2019: 165-170 - [c54]Jinyong Hou, Xuejie Ding, Jeremiah D. Deng, Stephen Cranefield:
Unsupervised Domain Adaptation using Deep Networks with Cross-Grafted Stacks. ICCV Workshops 2019: 3257-3264 - [i2]Jinyong Hou, Xuejie Ding, Jeremiah D. Deng:
Unsupervised Domain Adaptation using Deep Networks with Cross-Grafted Stacks. CoRR abs/1902.06328 (2019) - 2018
- [j19]Xiao Fang Liu, Zhi-Hui Zhan, Jeremiah D. Deng, Yun Li, Tianlong Gu, Jun Zhang:
An Energy Efficient Ant Colony System for Virtual Machine Placement in Cloud Computing. IEEE Trans. Evol. Comput. 22(1): 113-128 (2018) - [j18]Qiang Yang, Wei-Neng Chen, Jeremiah Da Deng, Yun Li, Tianlong Gu, Jun Zhang:
A Level-Based Learning Swarm Optimizer for Large-Scale Optimization. IEEE Trans. Evol. Comput. 22(4): 578-594 (2018) - [c53]Sean Hsin-Shyuan Lee, Jeremiah D. Deng, Martin K. Purvis, Maryam Purvis:
Hierarchical Population-Based Learning for Optimal Large-Scale Coalition Structure Generation in Smart Grids. Australasian Conference on Artificial Intelligence 2018: 16-28 - [c52]Sophie Zareei, Jeremiah D. Deng:
Impact of Compression Ratio and Reconstruction Methods on ECG Classification for E-Health Gadgets: A Preliminary Study. Australasian Conference on Artificial Intelligence 2018: 85-97 - [c51]Sean Hsin-Shyuan Lee, Jeremiah D. Deng, Martin K. Purvis, Maryam Purvis, Lizhi Peng:
An Improved PBIL Algorithm for Optimal Coalition Structure Generation of Smart Grids. PAKDD (Workshops) 2018: 345-356 - 2017
- [j17]Qiang Yang, Wei-Neng Chen, Tianlong Gu, Huaxiang Zhang, Jeremiah D. Deng, Yun Li, Jun Zhang:
Segment-Based Predominant Learning Swarm Optimizer for Large-Scale Optimization. IEEE Trans. Cybern. 47(9): 2896-2910 (2017) - [j16]Qunfeng Liu, Wei-Neng Chen, Jeremiah D. Deng, Tianlong Gu, Huaxiang Zhang, Zhengtao Yu, Jun Zhang:
Benchmarking Stochastic Algorithms for Global Optimization Problems by Visualizing Confidence Intervals. IEEE Trans. Cybern. 47(9): 2924-2937 (2017) - [c50]Sean Hsin-Shyuan Lee, Jeremiah D. Deng, Lizhi Peng, Martin K. Purvis, Maryam Purvis:
Top-k Merit Weighting PBIL for Optimal Coalition Structure Generation of Smart Grids. ICONIP (4) 2017: 171-181 - [c49]Ahmad Shahi, Jeremiah D. Deng, Brendon J. Woodford:
Online Hidden Conditional Random Fields to Recognize Activity-Driven Behavior Using Adaptive Resilient Gradient Learning. ICONIP (1) 2017: 515-525 - [c48]Ahmad Shahi, Jeremiah D. Deng, Brendon J. Woodford:
A streaming ensemble classifier with multi-class imbalance learning for activity recognition. IJCNN 2017: 3983-3990 - [c47]Sophie Zareei, Amir Hosein Afshar Sedigh, Jeremiah D. Deng, Martin K. Purvis:
Buffer management using integrated queueing models for mobile energy harvesting sensors. PIMRC 2017: 1-5 - 2016
- [c46]Jeremiah D. Deng:
Online Outlier Detection of Energy Data Streams Using Incremental and Kernel PCA Algorithms. ICDM Workshops 2016: 390-397 - [c45]Sepideh Zareei, Jeremiah D. Deng:
Energy management policy for fitness gadgets: A case study of human daily routines. ITNAC 2016: 13-18 - [c44]Xianbin Gu, Jeremiah D. Deng, Martin K. Purvis:
A hierarchical segmentation tree for superpixel-based image segmentation. IVCNZ 2016: 1-6 - [c43]Hanhe Lin, Jeremiah D. Deng, Brendon J. Woodford, Ahmad Shahi:
Online Weighted Clustering for Real-time Abnormal Event Detection in Video Surveillance. ACM Multimedia 2016: 536-540 - [c42]Hanhe Lin, Jeremiah D. Deng, Brendon J. Woodford:
Shot Boundary Detection Using Multi-instance Incremental and Decremental One-Class Support Vector Machine. PAKDD (1) 2016: 165-176 - [i1]Xianbin Gu, Jeremiah D. Deng, Martin K. Purvis:
Image segmentation with superpixel-based covariance descriptors in low-rank representation. CoRR abs/1605.05466 (2016) - 2015
- [j15]Jeremiah D. Deng, Martin K. Purvis:
Teaching Service Modelling to a Mixed Class: An Integrated Approach. Informatics Educ. 14(1): 37-52 (2015) - [j14]Munir Shah, Jeremiah D. Deng, Brendon J. Woodford:
A Self-adaptive CodeBook (SACB) model for real-time background subtraction. Image Vis. Comput. 38: 52-64 (2015) - [j13]Yuwei Xu, Jeremiah D. Deng, Mariusz Nowostawski, Martin K. Purvis:
Optimized routing for video streaming in multi-hop wireless networks using analytical capacity estimation. J. Comput. Syst. Sci. 81(1): 145-157 (2015) - [j12]Femi A. Aderohunmu, Davide Brunelli, Jeremiah D. Deng, Martin K. Purvis:
A Data Acquisition Protocol for a Reactive Wireless Sensor Network Monitoring Application. Sensors 15(5): 10221-10254 (2015) - [c41]Adeel Javed, Zhiyi Huang, Haibo Zhang, Jeremiah D. Deng:
CAMS: Consensus-Based Anchor-Node Management Scheme for Train Localisation. ADHOC-NOW 2015: 107-120 - [c40]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 - [c39]Hanhe Lin, Jeremiah D. Deng, Brendon J. Woodford:
Anomaly detection in crowd scenes via online adaptive one-class support vector machines. ICIP 2015: 2434-2438 - [c38]Sameer Khan, Suet-Peng Yong, Jeremiah D. Deng:
Ensemble classification with modified SIFT descriptor for medical image modality. IVCNZ 2015: 1-6 - 2014
- [j11]Munir Shah, Jeremiah D. Deng, Brendon J. Woodford:
Video background modeling: recent approaches, issues and our proposed techniques. Mach. Vis. Appl. 25(5): 1105-1119 (2014) - [c37]Adeel Javed, Haibo Zhang, Zhiyi Huang, Jeremiah D. Deng:
BWS: Beacon-driven wake-up scheme for train localization using wireless sensor networks. ICC 2014: 276-281 - [c36]Xianbin Gu, Jeremiah D. Deng, Martin K. Purvis:
Improving superpixel-based image segmentation by incorporating color covariance matrix manifolds. ICIP 2014: 4403-4406 - [c35]Jeremiah D. Deng:
Empirical capacity modeling and evaluation of delay tolerant network routing protocols. IPCCC 2014: 1-2 - [c34]Xianbin Gu, Jeremiah D. Deng, Martin K. Purvis:
Superpixel-based Segmentation using Multi-layer Bipartite Graphs and Grassmann Manifolds. IVCNZ 2014: 119 - [c33]Hanhe Lin, Jeremiah D. Deng, Brendon J. Woodford:
Spatial-Temporal Pyramid Matching for Crowd Scene Analysis. MLSDA@PRICAI 2014: 12 - [c32]Jeremiah D. Deng, Hsin-Shyuan Lee, Cameron McMillan, Aysha P. Rimoni, Ming Zhang:
Analyzing Wind Speed Data through Markov Chain based Profiling and Clustering. MLSDA@PRICAI 2014: 67 - [e3]Ashfaqur Rahman, Jeremiah D. Deng, Jiuyong Li:
Proceedings of the MLSDA 2014 2nd Workshop on Machine Learning for Sensory Data Analysis, Gold Coast, Australia, QLD, Australia, December 2, 2014. ACM 2014, ISBN 978-1-4503-3159-3 [contents] - 2013
- [j10]Suet-Peng Yong, Jeremiah D. Deng, Martin K. Purvis:
Wildlife video key-frame extraction based on novelty detection in semantic context. Multim. Tools Appl. 62(2): 359-376 (2013) - [j9]Genliang Guan, Zhiyong Wang, Shiyang Lu, Jeremiah Da Deng, David Dagan Feng:
Keypoint-Based Keyframe Selection. IEEE Trans. Circuits Syst. Video Technol. 23(4): 729-734 (2013) - [c31]Jeremiah D. Deng, Yue Zhang:
Light-weight Online Predictive Data Aggregation for Wireless Sensor Networks. MLSDA@AUS-AI 2013: 35 - [c30]Hanhe Lin, Jeremiah D. Deng, Brendon J. Woodford:
Event Detection Using Quantized Binary Code and Spatial-Temporal Locality Preserving Projections. Australasian Conference on Artificial Intelligence 2013: 123-134 - [c29]Munir Shah, Jeremiah D. Deng, Brendon J. Woodford:
Growing Neural Gas Video Background Model (GNG-BM). Australasian Conference on Artificial Intelligence 2013: 135-147 - [c28]Femi A. Aderohunmu, Giacomo Paci, Davide Brunelli, Jeremiah D. Deng, Luca Benini, Martin K. Purvis:
Trade-offs of Forecasting Algorithm for Extending WSN Lifetime in a Real-World Deployment. DCOSS 2013: 283-285 - [c27]Femi A. Aderohunmu, Giacomo Paci, Davide Brunelli, Jeremiah D. Deng, Luca Benini, Martin K. Purvis:
An Application-Specific Forecasting Algorithm for Extending WSN Lifetime. DCOSS 2013: 374-381 - [c26]Munir Shah, Jeremiah D. Deng, Brendon J. Woodford:
Improving Mixture of Gaussians background model through adaptive learning and Spatio-Temporal voting. ICIP 2013: 3436-3440 - [c25]Yuwei Xu, Jeremiah D. Deng, Mariusz Nowostawski:
Quality of service for video streaming over multi-hop wireless networks: Admission control approach based on analytical capacity estimation. ISSNIP 2013: 345-350 - [c24]Femi A. Aderohunmu, Giacomo Paci, Davide Brunelli, Jeremiah D. Deng, Luca Benini:
Prolonging the lifetime of wireless sensor networks using light-weight forecasting algorithms. ISSNIP 2013: 461-466 - [c23]Femi A. Aderohunmu, Giacomo Paci, Luca Benini, Jeremiah D. Deng, Davide Brunelli:
SWIFTNET: A data acquisition protocol for fast-reactive monitoring applications. SIES 2013: 93-96 - [e2]Jeremiah D. Deng, Haibo Zhang:
Workshop on Machine Learning for Sensory Data Analysis, MLSDA '13, Dunedin, New Zealand, December 2, 2013. ACM 2013, ISBN 978-1-4503-2513-4 [contents] - 2012
- [j8]Suet-Peng Yong, Jeremiah D. Deng, Martin K. Purvis:
Novelty detection in wildlife scenes through semantic context modelling. Pattern Recognit. 45(9): 3439-3450 (2012) - [c22]Munir Shah, Jeremiah D. Deng, Brendon J. Woodford:
Illumination Invariant Background Model Using Mixture of Gaussians and SURF Features. ACCV Workshops (1) 2012: 308-314 - [c21]Yuwei Xu, Jeremiah D. Deng, Mariusz Nowostawski:
Optimizing Routing in Multi-hop Wireless Networks Using Analytical Capacity Estimation: A Study on Video Streaming. HPCC-ICESS 2012: 748-755 - [c20]Femi A. Aderohunmu, Jeremiah D. Deng, Martin K. Purvis:
Optimization of Energy-efficient Protocols with Energy-heterogeneity for Coverage Preservation in Wireless Sensor Networks: An Empirical Study. HPCC-ICESS 2012: 1173-1178 - [c19]Suet-Peng Yong, Jeremiah D. Deng, Martin K. Purvis:
Key-frame extraction of wildlife video based on semantic context modeling. IJCNN 2012: 1-8 - [c18]Munir Shah, Jeremiah D. Deng, Brendon J. Woodford:
Enhancing the mixture of Gaussians background model with local matching and local adaptive learning. IVCNZ 2012: 103-108 - [c17]Hanhe Lin, Jeremiah D. Deng, Brendon J. Woodford:
Video manifold modelling: finding the right parameter settings for anomaly detection. IVCNZ 2012: 168-173 - [e1]Brendan McCane, Steven Mills, Jeremiah D. Deng:
Image and Vision Computing New Zealand, IVCNZ '12, Dunedin, New Zealand - November 26 - 28, 2012. ACM 2012, ISBN 978-1-4503-1473-2 [contents] - 2011
- [j7]Femi A. Aderohunmu, Jeremiah D. Deng, Martin K. Purvis:
Enhancing Clustering in Wireless Sensor Networks with Energy Heterogeneity. Int. J. Bus. Data Commun. Netw. 7(4): 18-31 (2011) - [j6]Jeremiah D. Deng, Martin K. Purvis, Maryam Purvis:
Software Effort Estimation: Harmonizing Algorithms and Domain Knowledge in an Integrated Data Mining Approach. Int. J. Intell. Inf. Technol. 7(3): 41-53 (2011) - [j5]Jeremiah D. Deng, Martin K. Purvis:
Multi-core application performance optimization using a constrained tandem queueing model. J. Netw. Comput. Appl. 34(6): 1990-1996 (2011) - [c16]Munir Shah, Jeremiah D. Deng, Brendon J. Woodford:
Enhanced Codebook Model for Real-Time Background Subtraction. ICONIP (3) 2011: 449-458 - 2010
- [j4]Jeremiah D. Deng:
Controlling Chaotic Associative Memory for Multiple Pattern Retrieval. Cogn. Comput. 2(4): 257-264 (2010) - [c15]Suet-Peng Yong, Jeremiah D. Deng, Martin K. Purvis:
Modelling semantic context for novelty detection in wildlife scenes. ICME 2010: 1254-1259
2000 – 2009
- 2008
- [j3]Jeremiah D. Deng, Christian Simmermacher, Stephen Cranefield:
A Study on Feature Analysis for Musical Instrument Classification. IEEE Trans. Syst. Man Cybern. Part B 38(2): 429-438 (2008) - 2007
- [j2]Da Deng:
Content-based image collection summarization and comparison using self-organizing maps. Pattern Recognit. 40(2): 718-727 (2007) - [c14]Jeremiah D. Deng, Matthew T. Gleeson:
Automatic Sapstain Detection in Processed Timber. Australian Conference on Artificial Intelligence 2007: 637-641 - 2006
- [c13]Irena Koprinska, Da Deng, Felix Feger:
Image classification using labelled and unlabelled data. EUSIPCO 2006: 1-5 - [c12]Christian Simmermacher, Da Deng, Stephen Cranefield:
Feature Analysis and Classification of Classical Musical Instruments: An Empirical Study. ICDM 2006: 444-458 - 2005
- [c11]Da Deng, Jianhua Zhang:
Combining Multiple Precision-Boosted Classifiers for Indoor-Outdoor Scene Classification. ICITA (1) 2005: 720-725 - [c10]Da Deng, Heiko Wolf:
POISE - Achieving Content-Based Picture Organisation for Image Search Engines. KES (2) 2005: 1-7 - 2004
- [c9]Da Deng, Jianhua Zhang, Martin K. Purvis:
Visualisation and Comparison of Image Collections based on Self-organised Maps. ACSW 2004: 97-102 - [c8]Brendon J. Woodford, Da Deng, George L. Benwell:
A wavelet-based neuro-fuzzy system for data mining small image sets. ACSW 2004: 139-143 - [c7]Da Deng:
Braving the Semantic Gap: Mapping Visual Concepts from Images and Videos. ICDM 2004: 50-59 - [c6]Da Deng:
Content-based Comparison of Image Collections via Distance Measuring of Self-organised Maps. MMM 2004: 233-240 - 2003
- [j1]Da Deng, Nikola K. Kasabov:
On-line pattern analysis by evolving self-organizing maps. Neurocomputing 51: 87-103 (2003) - 2001
- [c5]Da Deng, Nikola K. Kasabov:
An evolving localised learning model for on-line image colour quantisation. ICIP (1) 2001: 906-909 - 2000
- [c4]Da Deng, Nikola K. Kasabov:
ESOM: An Algorithm to Evolve Self-Organizing Maps from On-Line Data Streams. IJCNN (6) 2000: 3-8
1990 – 1999
- 1999
- [c3]Zhiyong Wang, Zheru Chi, Jeremiah Da Deng, Yinlin Yu:
Block-Constrained Fractal Coding Scheme for Image Retrieval. VISUAL 1999: 673-660 - 1995
- [c2]Da Deng, Kwok Ping Chan, Y. L. Yu:
Self-organising learning of receptive fields in multi-resolution. ICNN 1995: 2831-2834 - 1994
- [c1]Da Deng, Kwok Ping Chan, Yinglin Yu:
Handwritten Chinese Character Recognition Using Spatial Gabor Filters and Self-Organizing Feature Maps. ICIP (3) 1994: 940-944
Coauthor Index
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