Mark Johnston

发表

Fast Unsupervised Edge Detection Using Genetic Programming [Application Notes]

Mark Johnston, Mengjie Zhang, Bing Xue, 2018, IEEE Comput. Intell. Mag..

Particle swarm optimisation based AdaBoost for object detection

Mark Johnston, Mengjie Zhang, Ammar W. Mohemmed, 2011, Soft Comput..

A PSO Based Adaboost Approach to Object Detection

Mark Johnston, Mengjie Zhang, Ammar W. Mohemmed, 2008, SEAL.

An analysis of multi-sampled issue and no-replacement tournament selection

Mark Johnston, Mengjie Zhang, Peter Andreae, 2008, GECCO '08.

Effects of static and dynamic topologies in Particle Swarm Optimisation for edge detection in noisy images

Mark Johnston, Mengjie Zhang, Mahdi Setayesh, 2012, 2012 IEEE Congress on Evolutionary Computation.

Evolving Diverse Ensembles Using Genetic Programming for Classification With Unbalanced Data

Mark Johnston, Xin Yao, Mengjie Zhang, 2013, IEEE Transactions on Evolutionary Computation.

Binary Image Classification: A Genetic Programming Approach to the Problem of Limited Training Instances

Mark Johnston, Mengjie Zhang, Harith Al-Sahaf, 2016, Evolutionary Computation.

Genetic Programming for Extracting Edge Features Using Two Blocks

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2015, AusDM.

Feature Construction and Dimension Reduction Using Genetic Programming

Mark Johnston, Mengjie Zhang, Kourosh Neshatian, 2007, Australian Conference on Artificial Intelligence.

A Relaxed Approach to Simplification in Genetic Programming

Mark Johnston, Mengjie Zhang, Thomas Liddle, 2010, EuroGP.

Multi-Objective Genetic Programming for Classification with Unbalanced Data

Mark Johnston, Mengjie Zhang, Urvesh Bhowan, 2009, Australasian Conference on Artificial Intelligence.

Evolving "less-myopic" scheduling rules for dynamic job shop scheduling with genetic programming

Mark Johnston, Mengjie Zhang, Rachel Hunt, 2014, GECCO.

A Computational Study of Representations in Genetic Programming to Evolve Dispatching Rules for the Job Shop Scheduling Problem

Mark Johnston, Mengjie Zhang, Kay Chen Tan, 2013, IEEE Transactions on Evolutionary Computation.

Differentiating between individual class performance in Genetic Programming fitness for classification with unbalanced data

Mark Johnston, Mengjie Zhang, Urvesh Bhowan, 2009, 2009 IEEE Congress on Evolutionary Computation.

Is the not-sampled issue in tournament selection critical?

Mark Johnston, Mengjie Zhang, Peter Andreae, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

A novel particle swarm optimisation approach to detecting continuous, thin and smooth edges in noisy images

Mark Johnston, Mengjie Zhang, Mahdi Setayesh, 2013, Inf. Sci..

Automatic Programming via Iterated Local Search for Dynamic Job Shop Scheduling

Mark Johnston, Mengjie Zhang, Kay Chen Tan, 2015, IEEE Transactions on Cybernetics.

Dynamic Multi-objective Job Shop Scheduling: A Genetic Programming Approach

Mark Johnston, Mengjie Zhang, Kay Chen Tan, 2013, Automated Scheduling and Planning.

Automatic Design of Scheduling Policies for Dynamic Multi-objective Job Shop Scheduling via Cooperative Coevolution Genetic Programming

Mark Johnston, Mengjie Zhang, Kay Chen Tan, 2014, IEEE Transactions on Evolutionary Computation.

Learning iterative dispatching rules for job shop scheduling with genetic programming

Mark Johnston, Mengjie Zhang, Kay Chen Tan, 2013, The International Journal of Advanced Manufacturing Technology.

A genetic programming based hyper-heuristic approach for combinatorial optimisation

Mark Johnston, Mengjie Zhang, Su Nguyen, 2011, GECCO '11.

Developing New Fitness Functions in Genetic Programming for Classification With Unbalanced Data

Mark Johnston, Mengjie Zhang, Urvesh Bhowan, 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

AUC analysis of the pareto-front using multi-objective GP for classification with unbalanced data

Mark Johnston, Mengjie Zhang, Urvesh Bhowan, 2010, GECCO '10.

Genetic Programming for Classification with Unbalanced Data

Mark Johnston, Mengjie Zhang, Urvesh Bhowan, 2010, EuroGP.

Genetic programming for image classification with unbalanced data

Mark Johnston, Mengjie Zhang, Urvesh Bhowan, 2009, 2009 24th International Conference Image and Vision Computing New Zealand.

Reusing Genetic Programming for Ensemble Selection in Classification of Unbalanced Data

Mark Johnston, Xin Yao, Mengjie Zhang, 2014, IEEE Transactions on Evolutionary Computation.

Using Numerical Simplification to Control Bloat in Genetic Programming

Mark Johnston, Mengjie Zhang, David Kinzett, 2008, SEAL.

Investigation of simplification threshold and noise level of input data in numerical simplification of genetic programs

Mark Johnston, Mengjie Zhang, David Kinzett, 2010, IEEE Congress on Evolutionary Computation.

Numerical simplification for bloat control and analysis of building blocks in genetic programming

Mark Johnston, Mengjie Zhang, David Kinzett, 2009, Evol. Intell..

A Variant Program Structure in Tree-Based Genetic Programming for Multiclass Object Classification

Mark Johnston, Mengjie Zhang, Mengjie Zhang, 2009 .

Genetic Programming for Evolving Due-Date Assignment Models in Job Shop Environments

Mark Johnston, Mengjie Zhang, Kay Chen Tan, 2014, Evolutionary Computation.

Image descriptor: A genetic programming approach to multiclass texture classification

Mark Johnston, Mengjie Zhang, Brijesh Verma, 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

Automatically Evolving Rotation-Invariant Texture Image Descriptors by Genetic Programming

Ausama Al-Sahaf, Bing Xue, Mark Johnston, 2017, IEEE Transactions on Evolutionary Computation.

Keypoints Detection and Feature Extraction: A Dynamic Genetic Programming Approach for Evolving Rotation-Invariant Texture Image Descriptors

Ausama Al-Sahaf, Mark Johnston, Mengjie Zhang, 2017, IEEE Transactions on Evolutionary Computation.

Evolutionary Image Descriptor: A Dynamic Genetic Programming Representation for Feature Extraction

Mark Johnston, Mengjie Zhang, Harith Al-Sahaf, 2015, GECCO.

Genetic Programming Evolved Filters from a Small Number of Instances for Multiclass Texture Classification

Mark Johnston, Mengjie Zhang, Harith Al-Sahaf, 2014, IVCNZ '14.

Unsupervised learning for edge detection using Genetic Programming

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

A One-Shot Learning Approach to Image Classification Using Genetic Programming

Mark Johnston, Mengjie Zhang, Harith Al-Sahaf, 2013, Australasian Conference on Artificial Intelligence.

Binary image classification using genetic programming based on local binary patterns

Mark Johnston, Mengjie Zhang, Harith Al-Sahaf, 2013, 2013 28th International Conference on Image and Vision Computing New Zealand (IVCNZ 2013).

How online simplification affects building blocks in genetic programming

Mark Johnston, Mengjie Zhang, David Kinzett, 2009, GECCO.

Particle Swarm Optimization based Adaboost for face detection

Mark Johnston, Mengjie Zhang, Ammar W. Mohemmed, 2009, 2009 IEEE Congress on Evolutionary Computation.

Genetic Programming for Multiclass Texture Classification Using a Small Number of Instances

Mark Johnston, Mengjie Zhang, Harith Al-Sahaf, 2014, SEAL.

Bayesian genetic programming for edge detection

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2019, Soft Comput..

Bayesian genetic programming for edge detection

Wenlong Fu, Mengjie Zhang, Mark Johnston, 2018, Soft Computing.

Genetic programming for edge detection: a Gaussian-based approach

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2016, Soft Comput..

Genetic programming for edge detection: a Gaussian-based approach

Wenlong Fu, Mengjie Zhang, Mark Johnston, 2015, Soft Computing.

Automatic Resolution Selection for Edge Detection Using Genetic Programming

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2014, SEAL.

Distribution-based invariant feature construction using genetic programming for edge detection

Mengjie Zhang, Wenlong Fu, Mark Johnston, 2014, Soft Computing.

Low-Level Feature Extraction for Edge Detection Using Genetic Programming

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2014, IEEE Transactions on Cybernetics.

Is a Single Image Sufficient for Evolving Edge Features by Genetic Programming?

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2014, EvoApplications.

Gaussian mixture models and information entropy for image segmentation using particle swarm optimisation

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2013, 2013 28th International Conference on Image and Vision Computing New Zealand (IVCNZ 2013).

Investigation of low-level edge feature extraction using three blocks

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2013, 2013 28th International Conference on Image and Vision Computing New Zealand (IVCNZ 2013).

Genetic programming for edge detection using multivariate density

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2013, GECCO '13.

Triangular-distribution-based feature construction using Genetic Programming for edge detection

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2013, 2013 IEEE Congress on Evolutionary Computation.

Genetic Programming for Automatic Construction of Variant Features in Edge Detection

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2013, EvoApplications.

Automatic Construction of Gaussian-Based Edge Detectors Using Genetic Programming

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2013, EvoApplications.

Figure of Merit Based Fitness Functions in Genetic Programming for Edge Detection

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2012, SEAL.

Automatic Construction of Invariant Features Using Genetic Programming for Edge Detection

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2012, Australasian Conference on Artificial Intelligence.

Multi-frequency transformation for edge detection

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2012, IVCNZ '12.

Genetic programming for edge detection based on figure of merit

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2012, GECCO '12.

Genetic programming for edge detection using blocks to extract features

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2012, GECCO '12.

Soft edge maps from edge detectors evolved by genetic programming

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2012, 2012 IEEE Congress on Evolutionary Computation.

Genetic programming for edge detection via balancing individual training images

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2012, 2012 IEEE Congress on Evolutionary Computation.

Genetic Programming for Edge Detection Based on Accuracy of Each Training Image

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2011, Australasian Conference on Artificial Intelligence.

Genetic programming for edge detection: A global approach

Mark Johnston, Mengjie Zhang, Wenlong Fu, 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

Population statistics for particle swarm optimization: Single-evaluation methods in noisy optimization problems

Mark Johnston, Mengjie Zhang, Juan Rada-Vilela, 2015, Soft Comput..

Evolving Ensembles of Dispatching Rules Using Genetic Programming for Job Shop Scheduling

Mark Johnston, Mengjie Zhang, Su Nguyen, 2015, EuroGP.

Genetic programming for job shop scheduling

Mark Johnston, Mengjie Zhang, Kay Chen Tan, 2018, Studies in Computational Intelligence.

Genetic Programming Based Hyper-heuristics for Dynamic Job Shop Scheduling: Cooperative Coevolutionary Approaches

Gang Chen, Mark Johnston, Yi Mei, 2016, EuroGP.

Using Local Search to Evaluate Dispatching Rules in Dynamic Job Shop Scheduling

Mark Johnston, Mengjie Zhang, Rachel Hunt, 2015, EvoCOP.

Developing a Hyper-Heuristic Using Grammatical Evolution and the Capacitated Vehicle Routing Problem

Mark Johnston, Mengjie Zhang, Richard J. Marshall, 2014, SEAL.

Enhancing Heuristics for Order Acceptance and Scheduling Using Genetic Programming

Mark Johnston, Mengjie Zhang, Su Nguyen, 2014, SEAL.

A Comparison between Two Evolutionary Hyper-Heuristics for Combinatorial Optimisation

Mark Johnston, Mengjie Zhang, Richard J. Marshall, 2014, SEAL.

Reusing Genetic Programming for Ensemble Selection in Classification of Unbalanced Data

X. Yao, Mengjie Zhang, Mark Johnston, 2014, IEEE Transactions on Evolutionary Computation.

A sequential genetic programming method to learn forward construction heuristics for order acceptance and scheduling

Mark Johnston, Mengjie Zhang, Su Nguyen, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

Evolving machine-specific dispatching rules for a two-machine job shop using genetic programming

Mark Johnston, Mengjie Zhang, Rachel Hunt, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

Enhancing Branch-and-Bound Algorithms for Order Acceptance and Scheduling with Genetic Programming

Mark Johnston, Mengjie Zhang, Su Nguyen, 2014, EuroGP.

The Best Things Don't Always Come in Small Packages: Constant Creation in Grammatical Evolution

Conor Ryan, R. Muhammad Atif Azad, C. Ryan, 2014, EuroGP.

Evolving Stochastic Dispatching Rules for Order Acceptance and Scheduling via Genetic Programming

Mark Johnston, Mengjie Zhang, Su Nguyen, 2013, Australasian Conference on Artificial Intelligence.

Hybrid evolutionary computation methods for quay crane scheduling problems

Mark Johnston, Mengjie Zhang, Kay Chen Tan, 2013, Comput. Oper. Res..

Comparing ensemble learning approaches in genetic programming for classification with unbalanced data

Mark Johnston, Mengjie Zhang, Urvesh Bhowan, 2013, GECCO.

Genetic programming for order acceptance and scheduling

Mark Johnston, Mengjie Zhang, Su Nguyen, 2013, 2013 IEEE Congress on Evolutionary Computation.

Learning Reusable Initial Solutions for Multi-objective Order Acceptance and Scheduling Problems with Genetic Programming

Mark Johnston, Mengjie Zhang, Kay Chen Tan, 2013, EuroGP.

Learning iterative dispatching rules for job shop scheduling with genetic programming

K. Tan, Su Nguyen, Mengjie Zhang, 2013, The International Journal of Advanced Manufacturing Technology.

Automatic Discovery of Optimisation Search Heuristics for Two Dimensional Strip Packing Using Genetic Programming

Mark Johnston, Mengjie Zhang, Kay Chen Tan, 2012, SEAL.

Local Search in Parallel Linear Genetic Programming for Multiclass Classification

Mark Johnston, Mengjie Zhang, Aaron Scoble, 2012, Australasian Conference on Artificial Intelligence.

A coevolution genetic programming method to evolve scheduling policies for dynamic multi-objective job shop scheduling problems

Mark Johnston, Mengjie Zhang, Kay Chen Tan, 2012, 2012 IEEE Congress on Evolutionary Computation.

Evolving Reusable Operation-Based Due-Date Assignment Models for Job Shop Scheduling with Genetic Programming

Mark Johnston, Mengjie Zhang, Kay Chen Tan, 2012, EuroGP.

Ensemble Learning and Pruning in Multi-Objective Genetic Programming for Classification with Unbalanced Data

Mark Johnston, Mengjie Zhang, Urvesh Bhowan, 2011, Australasian Conference on Artificial Intelligence.

Evolving ensembles in multi-objective genetic programming for classification with unbalanced data

Mark Johnston, Mengjie Zhang, Urvesh Bhowan, 2011, GECCO '11.

A Comparison of Classification Strategies in Genetic Programming with Unbalanced Data

Mark Johnston, Mengjie Zhang, Urvesh Bhowan, 2010, Australasian Conference on Artificial Intelligence.

Multi-Objective Genetic Programming for object detection

Mark Johnston, Mengjie Zhang, Thomas Liddle, 2010, IEEE Congress on Evolutionary Computation.

Analysis of Building Blocks with Numerical Simplification in Genetic Programming

Mark Johnston, Mengjie Zhang, David Kinzett, 2010, EuroGP.

Genetic Programming for Classification with Unbalanced Data

Mengjie Zhang, Mark Johnston, Urvesh Bhowan, 2010, EuroGP.

Edge and Corner Extraction Using Particle Swarm Optimisation

Mark Johnston, Mengjie Zhang, Mahdi Setayesh, 2010, Australasian Conference on Artificial Intelligence.

A Single Population Genetic Programming based Ensemble Learning Approach to Job Shop Scheduling

Mark Johnston, Mengjie Zhang, Su Nguyen, 2015, GECCO.

Selection Schemes in Surrogate-Assisted Genetic Programming for Job Shop Scheduling

Mark Johnston, Mengjie Zhang, Kay Chen Tan, 2014, SEAL.

Particle swarm optimization based multi-prototype ensembles

Mark Johnston, Mengjie Zhang, Ammar W. Mohemmed, 2009, GECCO.