| Comparing pointwise and listwise objective functions for random-forest-based learning-to-rank M Ibrahim, M Carman ACM Transactions on Information Systems (TOIS) 34 (4), 1-38, 2016 | 62 | 2016 |
| Transformer-Based Deep Learning Model for Stock Price Prediction: A Case Study on Bangladesh Stock Market T Muhammad, AB Aftab, M Ibrahim, MM Ahsan, MM Muhu, SI Khan, ... International Journal of Computational Intelligence and Applications 22 (1 …, 2023 | 59 | 2023 |
| MangoLeafBD: A comprehensive image dataset to classify diseased and healthy mango leaves SI Ahmed, M Ibrahim, M Nadim, MM Rahman, MM Shejunti, T Jabid, ... Data in Brief 47, 108941, 2023 | 54 | 2023 |
| Minimization of CTS of k-CNOT circuits for SSF and MSF model M Ibrahim, AR Chowdhury, HMH Babu 2008 IEEE International Symposium on Defect and Fault Tolerance of VLSI …, 2008 | 19 | 2008 |
| Identifying Selected Diseases of Leaves using Deep Learning and Transfer Learning Models A Mimi, S Fatema Tuj Zohura, M Ibrahim, RR Haque, O Farrok, T Jabid, ... Machine Graphics and Vision 32 (1), 55-71, 2023 | 14 | 2023 |
| An empirical comparison of random forest-based and other learning-to-rank algorithms M Ibrahim Pattern Analysis and Applications 23 (3), 1133-1155, 2020 | 13 | 2020 |
| Reducing correlation of random forest–based learning‐to‐rank algorithms using subsample size M Ibrahim Computational Intelligence 35 (4), 774-798, 2019 | 12 | 2019 |
| From tf-idf to learning-to-rank: An overview M Ibrahim, M Murshed Handbook of Research on Innovations in Information Retrieval, Analysis, and …, 2016 | 11 | 2016 |
| Undersampling techniques to re-balance training data for large scale learning-to-rank M Ibrahim, M Carman 10th Asia Information Retrieval Society Conference, 444-457, 2014 | 8 | 2014 |
| Plant Disease Detection using Region-Based Convolutional Neural Network H Rehana, M Ibrahim, MH Ali https://arxiv.org/abs/2303.09063, 1-23, 2023 | 7 | 2023 |
| Sampling non-relevant documents of training sets for learning-to-rank algorithms M Ibrahim International Journal of Machine Learning and Computing 10 (3), 406-415, 2020 | 7 | 2020 |
| Scalability and performance of random forest based learning-to-rank for information retrieval M Ibrahim ACM SIGIR Forum 51 (1), 73-74, 2017 | 7 | 2017 |
| Facial expression recognition using local composition pattern A Kalam, ME Haque, M Jashem, M Hasan, M Ibrahim, T Jabid Proceedings of the 7th International Conference on Computer and …, 2019 | 6 | 2019 |
| Improving Scalability and Performance of Random Forest Based Learning-to-Rank Algorithms by Aggressive Subsampling. M Ibrahim, MJ Carman 12th Australasian Data Mining Conference (AusDM), 91-99, 2014 | 6 | 2014 |
| Crime Prediction using Machine Learning with a Novel Crime Dataset FT Shohan, AU Akash, M Ibrahim, MS Alam arXiv preprint arXiv:2211.01551, 2022 | 5 | 2022 |
| Understanding Bias and Variance of Learning-to-Rank Algorithms: An Empirical Framework M Ibrahim Applied Artificial Intelligence 36 (1), 1-34, 2021 | 5 | 2021 |
| Selecting Update Blocks of Convolutional Neural Networks using Genetic Algorithm in Transfer Learning MM Hasan, M Ibrahim, MS Ali Machine Graphics and Vision 33 (2), 1-16, 2024 | 4* | 2024 |
| Feature Selection for Learning-to-Rank using Simulated Annealing M Allvi, M Hasan, L Rayan, M Shahabuddin, MM Khan, M Ibrahim International Journal of Advanced Computer Science and Applications (IJACSA …, 2020 | 4 | 2020 |
| On Evaluation of Patrolling and Signalling Schemes to Prevent Poaching in Green Security Games DT Hasan, MM Khan, M Ibrahim, I Almansour Intelligent Systems with Applications 14, 1-15, 2022 | 3 | 2022 |
| Evolution of Random Forest from Decision Tree and Bagging: A Bias-Variance Perspective M Ibrahim Dhaka University Journal of Applied Sciences and Engineering (DUJASE) 7 (1 …, 2022 | 3 | 2022 |
Md.Sawkat AliAssociate Professor, East West University, Dhaka, Bangladeshewubd.edu üzerinde doğrulanmış e-posta adresine sahip
