C. Omlin

发表

Inserting rules into recurrent neural networks

C. L. Giles, Christian W. Omlin, Colin Giles, 1992, Neural Networks for Signal Processing II Proceedings of the 1992 IEEE Workshop.

Local versus global segmentation for facial expression recognition

Jacob Whitehill, Christian W. Omlin, C. Omlin, 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

An architecture for encoding two-dimensional cyclone track prediction problem in coevolutionary recurrent neural networks

Rohitash Chandra, Christian W. Omlin, Ratneel Deo, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

A Machine Learning Method for Extracting Symbolic Knowledge from Recurrent Neural Networks

Christian W. Omlin, A. Vahed, C. Omlin, 2004, Neural Computation.

Prediction of seismic events in mines using neural networks

C. Omlin, J. van Zyl, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

Pruning recurrent neural networks for improved generalization performance

C. L. Giles, C. Lee Giles, Christian W. Omlin, 1994, Proceedings of IEEE Workshop on Neural Networks for Signal Processing.

Training Second-Order Recurrent Neural Networks using Hints

C. Lee Giles, Christian W. Omlin, C. Omlin, 1992, ML.

Remote sensing of mangroves using unmanned aerial vehicles: current state and future directions

C. Omlin, E. Zimudzi, I. Sanders, 2019, Journal of Spatial Science.

Chapter 16. Insertion of Prior Knowledge

C. Lee Giles, P. Frasconi, M. Gori, 2001 .

Chereme-Based Recognition of Isolated , Dynamic Gestures from South African Sign Language with Hidden Markov Models

C. Omlin, 2006 .

MCD: An End-to-end Multicast Congestion Detection Scheme using Support Vector Machines

C. Omlin, Xiaoming Liu, 2010 .

Recurrent Neural Networks for Signature Verification

Christian W. Omlin, C. Omlin, Conrad Tiflin, 2003 .

Evolutionary Training of Hybrid Systems of Recurrent Neural Networks and Hidden Markov Models

C. Omlin, Rohitash Chandra, 2008 .

Binary Feature Selection and Integration in Specialized Search Engines

C. Lee Giles, S. Lawrence, G. Flake, 2007 .

Reening Hidden Markov Models with Recurrent Neural Networks

C. Omlin, T. Wessels, 1999 .

Estimation of Wind Turbine Performance Degradation with Deep Neural Networks

Manuel S. Mathew, C. Omlin, S. Kandukuri, 2022, PHM Society European Conference.

Balancing Profit, Risk, and Sustainability for Portfolio Management

C. Omlin, Charl Maree, 2022, 2022 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr).

Automatic Sleep Stage Identification with Time Distributed Convolutional Neural Network

C. Omlin, M. Dutt, M. G. Olsen, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Towards Artificial Virtuous Agents: Games, Dilemmas and Machine Learning

C. Omlin, Ole-Christoffer Granmo, E. Bohn, 2022, 2208.14037.

Long Horizon Anomaly Prediction in Multivariate Time Series with Causal Autoencoders

J. Dittmann, C. Omlin, A. Khukhunaishvili, 2022, PHM Society European Conference.

Towards artificial virtuous agents: games, dilemmas and machine learning

C. Omlin, Ole-Christoffer Granmo, E. Bohn, 2022, AI and Ethics.

Controller Performance Monitoring: A Survey of Problems and a Review of Approaches from a Data-Driven Perspective with a Focus on Oscillations Detection and Diagnosis

C. Omlin, M. Aftab, Wahiba Bounoua, 2022, Industrial & Engineering Chemistry Research.

Getting to Grips with Support Vector Machines: Theory

Kroon Rs, Christian W. Omlin, C. Omlin, 2004 .

Reinforcement Learning Your Way: Agent Characterization through Policy Regularization

Charl Maree, Christian Omlin, C. Omlin, 2022, AI.

Symbolic Knowledge Representation in Recurrent Neural Networks: Insights from Theoretical Models of

C. Lee Giles, Christian W. Omlin, C. Omlin, 2000 .

Extraction, Insertion and Refinement of Symbolic Rules in Dynamically Driven Recurrent Neural Networks

C. Lee Giles, Christian W. Omlin, C. Omlin, 1993 .

Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunities pdf

Christian Omlin, Waddah Saeed, C. Omlin, 2021, Knowl. Based Syst..

Renosterveld Conservation in South Africa: A Case Study for Handling Uncertainty in Knowledge-Based Neural Networks for Environmental Management

Rohitash Chandra, Christian W. Omlin, R. Knight, 2009 .

The Comparison and Combination of Genetic and Gradient Descent Learning in Recurrent Neural Networks: An Application to Speech Phoneme Classification

Rohitash Chandra, Christian W. Omlin, C. Omlin, 2007, Artificial Intelligence and Pattern Recognition.

Inductive bias strength in knowledge-based neural networks: application to magnetic resonance spectroscopy of breast tissues

Christian W. Omlin, Sean Snyders, C. Omlin, 2003, Artif. Intell. Medicine.

Inductive Bias in Recurrent Neural Networks

C. Omlin, S. Snyders, 2001, IWANN.

Knowledge-Based Neural Networks for Modelling Time Series

Jacobus van Zyl, Christian W. Omlin, C. Omlin, 2001, IWANN.

What inductive bias gives good neural network training performance?

Christian W. Omlin, Sean Snyders, C. Omlin, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Refining hidden Markov models with recurrent neural networks

Christian W. Omlin, T. Wessels, C. Omlin, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Extracting salient features for network intrusion detection using machine learning methods

Ralf C. Staudemeyer, Christian W. Omlin, C. Omlin, 2014, South Afr. Comput. J..

Haar features for FACS AU recognition

Jacob Whitehill, Christian W. Omlin, C. Omlin, 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

Extraction of rules from discrete-time recurrent neural networks

C. Lee Giles, Christian W. Omlin, C. Omlin, 1996, Neural Networks.

Deep Crowd Anomaly Detection by Fusing Reconstruction and Prediction Networks

Md. Haidar Sharif, C. Omlin, Lei Jiao, 2023, Electronics.

Road Detection for Reinforcement Learning Based Autonomous Car

Rupsa Saha, Christian W. Omlin, Morten Goodwin, 2020, ICISS.

Learning, Representation, and Synthesis of Discrete Dynamical Systems in Continuous Recurrent Neural

C. Lee Giles, Christian W. Omlin, C. Omlin, 1995 .

Segmenting mangrove ecosystems drone images using SLIC superpixels

Nicholas Rollings, Edward Zimudzi, Christian Omlin, 2018, Geocarto International.

Rule extraction from recurrent neural networks using a symbolic machine learning algorithm

Christian W. Omlin, Anwar Vahed, C. Omlin, 1999, ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378).

Fuzzy finite-state automata can be deterministically encoded into recurrent neural networks

Karvel K. Thornber, C. Lee Giles, Christian W. Omlin, 1998, IEEE Trans. Fuzzy Syst..

Facial action unit intensity estimation using rotation invariant features and regression analysis

Turgay Çelik, Hima Vadapalli, Christian W. Omlin, 2014, 2014 IEEE International Conference on Image Processing (ICIP).

Constructing deterministic finite-state automata in recurrent neural networks

C. Lee Giles, Christian W. Omlin, C. Omlin, 1996, JACM.

Rule Revision With Recurrent Neural Networks

C. Lee Giles, Christian W. Omlin, C. Omlin, 1996, IEEE Trans. Knowl. Data Eng..

DEADLINER: building a new niche search engine

C. Lee Giles, Gary William Flake, Steve Lawrence, 2000, CIKM '00.

Clustering in Recurrent Neural Networks for Micro-Segmentation using Spending Personality

Christian W. Omlin, Charl Maree, C. Omlin, 2021, 2021 IEEE Symposium Series on Computational Intelligence (SSCI).

Automatic Detection of Film Orientation with Support Vector Machines

Christian W. Omlin, Dane Walsh, C. Omlin, 2002, IEA/AIE.

SleepXAI: An explainable deep learning approach for multi-class sleep stage identification

C. Omlin, Morten Goodwin, M. Dutt, 2022, Applied Intelligence.

Heuristics for the extraction of rules from discrete-time recurrent neural networks

C. L. Giles, Christian W. Omlin, C. B. Miller, 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

Equivalence in knowledge representation: automata, recurrent neural networks, and dynamical fuzzy systems

Karvel K. Thornber, C. L. Giles, Christian W. Omlin, 1999, Proc. IEEE.

Fuzzy Knowledge and Recurrent Neural Networks: A Dynamical Systems Perspective

Karvel K. Thornber, C. Lee Giles, Christian W. Omlin, 1998, Hybrid Neural Systems.

Constructing deterministic finite-state automata in sparse recurrent neural networks

C. L. Giles, Christian W. Omlin, Colin Giles, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

Professional Experience

C. Omlin, 1975 .

The Convolutional Tsetlin Machine pdf

Ole-Christoffer Granmo, Morten Goodwin Olsen, Lei Jiao, 2019, ArXiv.

Spatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeter

J. Dittmann, K. Maeshima, C. Omlin, 2023, 2311.04190.

Determining Cluster Boundaries using Particle Swarm Optimization

C. Omlin, Anurag Sharma, 2008 .

Stable Encoding of Large Finite-State Automata in Recurrent Neural Networks with Sigmoid Discriminants

C. Lee Giles, Christian W. Omlin, C. Omlin, 1996, Neural Computation.

Sleep Stage Identification based on Single-Channel EEG Signals using 1-D Convolutional Autoencoders

C. Omlin, M. Dutt, Surender Redhu, 2022, 2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom).

Lightweight Multi-System Multivariate Interconnection and Divergence Discovery

J. Dittmann, C. Omlin, S. Cooper, 2024, 2404.08453.

CNN-ViT Supported Weakly-Supervised Video Segment Level Anomaly Detection

Md. Haidar Sharif, C. Omlin, Lei Jiao, 2023, Sensors.

Data driven approach for the management of wind and solar energy integrated electrical distribution network with high penetration of electric vehicles

C. Omlin, M. Kolhe, S. Kandukuri, 2023, Journal of Cleaner Production.