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Jani, Md Rafsan
Jani, Md Rafsan
Other namesRafsanjani Muhammod, Muhammod Rafsanjani
Ph. D. Student at Drexel University
Verified email at drexel.edu - Homepage
Title
Cited by
Cited by
Year
Identification and Recognition of Rice Diseases and Pests Using Deep Convolutional Neural Networks
R Rahman, P Arko, E Ali, M Khan, A Wasif, MR Jani, MS Kabir
https://arxiv.org/pdf/1812.01043v1.pdf, 27, 2019
388*2019
Cusboost: Cluster-based under-sampling with boosting for imbalanced classification
F Rayhan, S Ahmed, A Mahbub, R Jani, S Shatabda, DM Farid
2017 2nd International Conference on Computational Systems and Information …, 2017
1032017
PyFeat: a Python-based effective feature generation tool for DNA, RNA and protein sequences
R Muhammod, S Ahmed, D Md Farid, S Shatabda, A Sharma, A Dehzangi
Bioinformatics 35 (19), 3831-3833, 2019
1022019
Hybrid methods for class imbalance learning employing bagging with sampling techniques
S Ahmed, A Mahbub, F Rayhan, R Jani, S Shatabda, DM Farid
2017 2nd International Conference on Computational Systems and Information …, 2017
452017
ACP-MHCNN: an accurate multi-headed deep-convolutional neural network to predict anticancer peptides
S Ahmed, R Muhammod, ZH Khan, S Adilina, A Sharma, S Shatabda, ...
Scientific Reports 11 (1), 1-15, 2021
422021
iPro70-FMWin: identifying Sigma70 promoters using multiple windowing and minimal features
MS Rahman, U Aktar, MR Jani, S Shatabda
Molecular Genetics and Genomics 294 (1), 69-84, 2019
412019
iPromoter-FSEn: Identification of bacterial σ70 promoter sequences using feature subspace based ensemble classifier
MS Rahman, U Aktar, MR Jani, S Shatabda
Genomics 111 (5), 1160-1166, 2019
402019
Meboost: Mixing estimators with boosting for imbalanced data classification
F Rayhan, S Ahmed, A Mahbub, MR Jani, S Shatabda, DM Farid, ...
2017 11th international conference on software, knowledge, information …, 2017
292017
LIUBoost: locality informed under-boosting for imbalanced data classification
S Ahmed, F Rayhan, A Mahbub, MR Jani, S Shatabda, DM Farid
Emerging Technologies in Data Mining and Information Security, 133-144, 2019
262019
iRecSpot-EF: effective sequence based features for recombination hotspot prediction
MR Jani, MTK Mozlish, S Ahmed, NS Tahniat, DM Farid, S Shatabda
Computers in biology and medicine 103, 17-23, 2018
232018
CluSem: Accurate clustering-based ensemble method to predict motor imagery tasks from multi-channel EEG data
MO Miah, R Muhammod, KA Al Mamun, DM Farid, S Kumar, A Sharma, ...
Journal of Neuroscience Methods 364, 109373, 2021
102021
SubFeat: Feature Subspacing Ensemble Classifier for Function Prediction of DNA, RNA and Protein Sequences
HMF Haque, M Rafsanjani, F Arifin, S Adilina, S Shatabda
Computational Biology and Chemistry, 107489, 2021
72021
Prediction of motor imagery tasks from multi-channel eeg data for brain-computer interface applications
MO Miah, MM Rahman, R Muhammod, DM Farid
BioRxiv, 2020.04. 08.032201, 2020
52020
Revisiting CNN for Highly Inflected Bengali and Hindi Language Modeling
CR Rahman, MD Rahman, M Rafsan, S Zakir, ME Ali, R Muhammod
arXiv preprint arXiv:2110.13032, 2021
12021
CNN for Modeling Sanskrit Originated Bengali and Hindi Language
C Rahman, MDH Rahman, M Rafsan, ME Ali, S Zakir, R Muhammod
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the …, 2022
2022
Paradigm Shift in Language Modeling: Revisiting CNN for Modeling Sanskrit Originated Bengali and Hindi Language
CR Rahman, MD Rahman, M Rafsan, S Zakir, ME Ali, R Muhammod
arXiv preprint arXiv:2110.13032, 2021
2021
Paradigm Shift in Language Modeling: Revisiting CNN for Modeling Sanskrit Originated Bengali and Hindi Language
C Rafeed Rahman, H Rahman, M Rafsan, S Zakir, M Eunus Ali, ...
arXiv e-prints, arXiv: 2110.13032, 2021
2021
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