Object Recognition Using Simulated Evolution on Fourier Descriptors. - Muhammad Sarfraz 001; Jawad Usman Arshed; Sajjad Ahmad Madani; Muhammad Iqbal 001 (WSC, 2009)

Automatically defined functions for learning classifier systems. - Muhammad Iqbal 001; Mengjie Zhang 001; Will N. Browne (GECCO (Companion), 2011)

XCSR with Computed Continuous Action. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (Australasian Conference on Artificial Intelligence, 2012)

Extracting and using building blocks of knowledge in learning classifier systems. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (GECCO, 2012)

Learning overlapping natured and niche imbalance boolean problems using XCS classifier systems. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (IEEE Congress on Evolutionary Computation, 2013)

Extending learning classifier system with cyclic graphs for scalability on complex, large-scale boolean problems. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (GECCO, 2013)

Comparison of two methods for computing action values in XCS with code-fragment actions. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (GECCO (Companion), 2013)

Learning complex, overlapping and niche imbalance Boolean problems using XCS-based classifier systems. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (Evol. Intell., 2013)

Special issue on advances in Learning Classifier Systems. - Kamran Shafi; Ryan J. Urbanowicz; Muhammad Iqbal 001 (Evol. Intell., 2013)

Evolving optimum populations with XCS classifier systems - XCS with code fragmented action. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (Soft Comput., 2013)

Salient object detection using learning classifiersystems that compute action mappings. - Muhammad Iqbal 001; Syed Saud Naqvi; Will N. Browne; Christopher Hollitt; Mengjie Zhang 001 (GECCO, 2014)

Reusing Building Blocks of Extracted Knowledge to Solve Complex, Large-Scale Boolean Problems. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (IEEE Trans. Evol. Comput., 2014)

Improving the Scalability of XCS-Based Learning Classifier Systems. - Muhammad Iqbal 001 (2014)

Special issue on the 20th anniversary of XCS. - Tim Kovacs; Muhammad Iqbal 001; Kamran Shafi; Ryan J. Urbanowicz (Evol. Intell., 2015)

Improving genetic search in XCS-based classifier systems through understanding the evolvability of classifier rules. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (Soft Comput., 2015)

Improving classification on images by extracting and transferring knowledge in genetic programming. - Muhammad Iqbal 001; Mengjie Zhang 001; Bing Xue 001 (CEC, 2016)

Evolutionary algorithms for classification of mammographie densities using local binary patterns and statistical features. - Francine Burling-Claridge; Muhammad Iqbal 001; Mengjie Zhang 001 (CEC, 2016)

Integration of code-fragment based learning classifier systems for multiple domain perception and learning. - Yi Liu 090; Muhammad Iqbal 001; Isidro M. Alvarez; Will N. Browne (CEC, 2016)

A comprehensive strategy for mammogram image classification using learning classifier systems. - Abubakar Siddique; Muhammad Iqbal 001; Will N. Browne (CEC, 2016)

Reusing Extracted Knowledge in Genetic Programming to Solve Complex Texture Image Classification Problems. - Muhammad Iqbal 001; Bing Xue 001; Mengjie Zhang 001 (PAKDD (2), 2016)

Learning feature fusion strategies for various image types to detect salient objects. - Muhammad Iqbal 001; Syed Saud Naqvi; Will N. Browne; Christopher Hollitt; Mengjie Zhang 001 (Pattern Recognit., 2016)

Text Classification Using Lifelong Machine Learning. - Muhammad Hassan Arif; Xin Jin; Jianxin Li 002; Muhammad Iqbal 001 (ICONIP (1), 2017)

Solving Social Media Text Classification Problems Using Code Fragment-Based XCSR. - Muhammad Hassan Arif; Jianxin Li 002; Muhammad Iqbal 001 (ICTAI, 2017)

Optimizing XCSR for Text Classification. - Muhammad Hassan Arif; Jianxin Li 002; Muhammad Iqbal 001; Hao Peng 001 (SOSE, 2017)

Extending XCS with Cyclic Graphs for Scalability on Complex Boolean Problems. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (Evol. Comput., 2017)

Cross-Domain Reuse of Extracted Knowledge in Genetic Programming for Image Classification. - Muhammad Iqbal 001; Bing Xue 001; Harith Al-Sahaf; Mengjie Zhang 001 (IEEE Trans. Evol. Comput., 2017)

Sentiment analysis and spam detection in short informal text using learning classifier systems. - Muhammad Hassan Arif; Jianxin Li 002; Muhammad Iqbal 001; Kaixu Liu (Soft Comput., 2018)

Extracting and reusing blocks of knowledge in learning classifier systems for text classification: a lifelong machine learning approach. - Muhammad Hassan Arif; Muhammad Iqbal 001; Jianxin Li 002 (Soft Comput., 2019)

Genetic programming with transfer learning for texture image classification. - Muhammad Iqbal 001; Harith Al-Sahaf; Bing Xue 001; Mengjie Zhang 001 (Soft Comput., 2019)

Learning Regular Expressions Using XCS-Based Classifier System. - Hafiz Asadul Rehman; Muhammad Iqbal 001; Irfan Younas; Maryam Bashir (Int. J. Pattern Recognit. Artif. Intell., 2020)

DeepShip: An underwater acoustic benchmark dataset and a separable convolution based autoencoder for classification. - Muhammad Irfan 009; Jiangbin Zheng 001; Shahid Ali; Muhammad Iqbal 001; Zafar Masood; Umar Hamid (Expert Syst. Appl., 2021)

Brain inspired lifelong learning model based on neural based learning classifier system for underwater data classification. - Muhammad Irfan 009; Jiangbin Zheng 001; Muhammad Iqbal 001; Zafar Masood; Muhammad Hassan Arif; Syed Rauf ul Hassan (Expert Syst. Appl., 2021)

A novel lifelong learning model based on cross domain knowledge extraction and transfer to classify underwater images. - Muhammad Irfan 009; Jiangbin Zheng 001; Muhammad Iqbal 001; Muhammad Hassan Arif (Inf. Sci., 2021)

Enhancing learning classifier systems through convolutional autoencoder to classify underwater images. - Muhammad Irfan 009; Jiangbin Zheng 001; Muhammad Iqbal 001; Muhammad Hassan Arif (Soft Comput., 2021)

Knowledge extraction and retention based continual learning by using convolutional autoencoder-based learning classifier system. - Muhammad Irfan 009; Jiangbin Zheng 001; Muhammad Iqbal 001; Zafar Masood; Muhammad Hassan Arif (Inf. Sci., 2022)

Attention in Rule-Based Machine Learning: Exploiting Learning Classifier Systems' Generalization for Image Classification. - Abubakar Siddique; Muhammad Iqbal 001; Shahab Ud Din; Will N. Browne (GECCO Companion, 2023)

A Survey on Learning Classifier Systems from 2022 to 2024. - Abubakar Siddique; Michael Heider; Muhammad Iqbal 001; Hiroki Shiraishi (GECCO Companion, 2024)

Enhancing Visual Focus: Incorporating Attention into Rule-Based Machine Learning. - Abubakar Siddique; Muhammad Iqbal 001; Will N. Browne (IVCNZ, 2024)

A Comprehensive Framework for Intelligent, Scalable, and Performance-Optimized Software Development. - Noor Arshad; Talal Ashraf Butt; Muhammad Iqbal 001 (IEEE Access, 2025)