Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions F Alsolami, M Azad, I Chikalov, M Moshkov Springer International Publishing, 2020 | 40 | 2020 |
Multi-stage optimization of decision and inhibitory trees for decision tables with many-valued decisions M Azad, M Moshkov European Journal of Operational Research 263 (3), 910-921, 2017 | 26 | 2017 |
Entropy-based greedy algorithm for decision trees using hypotheses M Azad, I Chikalov, S Hussain, M Moshkov Entropy 23 (7), 808, 2021 | 24 | 2021 |
RTF-RCNN: An architecture for real-time tomato plant leaf diseases detection in video streaming using Faster-RCNN M Alruwaili, MH Siddiqi, A Khan, M Azad, A Khan, S Alanazi Bioengineering 9 (10), 565, 2022 | 18 | 2022 |
Maximum entropy Markov model for human activity recognition using depth camera I Alrashdi, MH Siddiqi, Y Alhwaiti, M Alruwaili, M Azad IEEE Access 9, 160635-160645, 2021 | 17 | 2021 |
Optimization of decision trees with hypotheses for knowledge representation M Azad, I Chikalov, S Hussain, M Moshkov Electronics 10 (13), 1580, 2021 | 14 | 2021 |
Robustness Fine-Tuning Deep Learning Model for Cancers Diagnosis Based on Histopathology Image Analysis SA El-Ghany, M Azad, M Elmogy Diagnostics 13 (4), 699, 2023 | 13 | 2023 |
Decision rules derived from optimal decision trees with hypotheses M Azad, I Chikalov, S Hussain, M Moshkov, B Zielosko Entropy 23 (12), 1641, 2021 | 12 | 2021 |
Minimizing number of nodes in decision trees with hypotheses M Azad, I Chikalov, S Hussain, M Moshkov Procedia Computer Science 192, 232-240, 2021 | 12 | 2021 |
Minimizing depth of decision trees with hypotheses M Azad, I Chikalov, S Hussain, M Moshkov Rough Sets: International Joint Conference, IJCRS 2021, Bratislava, Slovakia …, 2021 | 12 | 2021 |
Multi-Pruning of Decision Trees for Knowledge Representation and Classification M Azad, I Chikalov, S Hussain, M Moshkov The 3rd IAPR Asian Conference on Pattern Recognition (ACPR2015), 2015 | 12 | 2015 |
Greedy Algorithm for Construction of Decision Trees for Tables with Many-Valued Decisions. M Azad, I Chikalov, M Moshkov, B Zielosko CS&P, 13-24, 2012 | 12 | 2012 |
Three approaches to deal with inconsistent decision tables-comparison of decision tree complexity M Azad, I Chikalov, M Moshkov Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing: 14th …, 2013 | 11 | 2013 |
Decision rules, trees and tests for tables with many-valued decisions–comparative study M Azad, B Zielosko, M Moshkov, I Chikalov Procedia Computer Science 22, 87-94, 2013 | 11 | 2013 |
Minimization of decision tree average depth for decision tables with many-valued decisions M Azad, M Moshkov Procedia Computer Science 35, 368-377, 2014 | 10 | 2014 |
[Retracted] A Precise Medical Imaging Approach for Brain MRI Image Classification MH Siddiqi, A Alsayat, Y Alhwaiti, M Azad, M Alruwaili, S Alanazi, ... Computational Intelligence and Neuroscience 2022 (1), 6447769, 2022 | 9 | 2022 |
Representation of knowledge by decision trees for decision tables with multiple decisions M Azad, I Chikalov, M Moshkov Procedia Computer Science 176, 653-659, 2020 | 8 | 2020 |
Classification and Optimization of Decision Trees for Inconsistent Decision Tables Represented as MVD Tables A Mohammad, M Mikhail Proceedings of the 2015 Federated Conference on Computer Science and …, 2015 | 8* | 2015 |
Minimization of decision tree depth for multi-label decision tables M Azad, M Moshkov 2014 IEEE International Conference on Granular Computing (GrC), 7-12, 2014 | 8 | 2014 |
A Bi-criteria optimization model for adjusting the decision tree parameters M Azad, M Moshkov Kuwait Journal of Science 49 (2), 2022 | 7 | 2022 |