📑 GOOGLE SCHOLAR CITATIONS & NUMBER OF PUBLICATIONS

📝 CONFERENCE PROCEEDINGS

[2024] S. Agarwala, S. Agarwala, A. Y. Srizon, S. M. Hasan, N. T. Esha, and F. Faruk, “Uncovering patterns of depression in engineering and medical students using machine learning,” in 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON), IEEE, 2024, pp. 921–926.

[2024] S. Agarwala, M. S. Ali, A. T. Quanita, et al., “Precision death forecasting of dengue outbreaks in bangladesh by blending statistical and machine learning models,” in 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON), IEEE, 2024, pp. 981–986.

[2024] S. Agarwala, A. S. Sajid, A. T. Quanita, M. S. Ali, and S. M. Hasan, “Enhancing dengue outbreak prediction in bangladesh: A comparative study of advanced predictive models,” in 2024 IEEE International Conference on Computing, Applications and Systems (COMPAS), IEEE, 2024, pp. 1–6.

[2024] T. T. Ahmmed, M. F. Faruk, A. Y. Srizon, et al., “Shallow tuned densenet: A lightweight convolutional neural network approach for enhanced skin lesion recognition,” in 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON), IEEE, 2024, pp. 1–6.

[2024] A. U. Alam, S. P. Islam, S. M. Hasan, et al., “Optic disc and cup segmentation via enhanced u-net with residual and attention mechanisms,” in 2024 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT), IEEE, 2024, pp. 329–334.

[2024] T. Das, S. M. Hasan, A. H. Efat, et al., “Towards superior eeg-based emotion recognition: Integrating cnn outputs with machine learning classifiers for enhanced performance,” in 2024 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT), IEEE, 2024, pp. 699–704.

[2024] J. Ferdaues, M. M. Islam, M. R. Hossain, et al., “The design and analysis of 5g mmwave backhaul communication channels with human obstruction and blockage considerations,” in 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON), IEEE, 2024, pp. 6–11.

[2024] T. Halder, A. Y. Srizon, N. T. Esha, S. M. Hasan, M. F. Faruk, and M. R. Hossain, “Enhancing email safety: Harnessing ml, dl, and llm models for spam detection,” in 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON), IEEE, 2024, pp. 1–6.

[2024] M. M. Hasib, M. F. Faruk, S. M. Hasan, et al., “Improved skin lesion detection with double layer concatenated densenet using transfer learning and attention modules,” in 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON), IEEE, 2024, pp. 1–6.

[2024] M. S.Hossain, S. M.Hasan, M. AlMamun, A. Y. Srizon, M. F. Faruk, and M. R.Hossain, “Optimizing depth and ego-motion estimation with swin transformer: A comprehensive study,” in 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON), IEEE, 2024, pp. 987–992.

[2024] M. M. Islam, F. Akter, M. R. Hossain, M. F. Hossain, S. M. Hasan, and M. A. Y. Srizon, “An advanced iot and gps-gsm based real-time automated data monitoring robot with image processing and live streaming for human life and land mine detection systems,” in 2024 International Conference on Computer, Electrical & Communication Engineering (ICCECE), IEEE, 2024, pp. 1–7.

[2024] I. Jahan, A. H. Efat, S. M.Hasan, et al., “An explainable deep learning framework for multi-class skin lesion classification while resolving class imbalance,” in 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON), IEEE, 2024, pp. 473–478.

[2024] N. Jannat, S. Mahedy Hasan, and M. F. Zibran, “Revolutionizing crop leaf disease detection: A novel ensemble learning framework using customized efficientnets,” in International Conference on Intelligent Systems and Pattern Recognition, Springer, 2024, pp. 114–129.

[2024] S. R. Kabir, A. Y. Srizon, N. T. Esha, et al., “Student distraction detection and concentration analysis via transfer learned convolutional neural networks,” in 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON), IEEE, 2024, pp. 1–6.

[2024] I. Khan, A. Y. Srizon, M. F. Faruk, et al., “Leveraging the robust capability of modified multi-layer gated recurrent units for fake news detection,” in 2024 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT), IEEE, 2024, pp. 986–991.

[2024] T. F. Nidhi, A. H. Efat, S. M. Hasan, M. S. U. Zaman, and A. N. Wasit, “Triple attention mobilenetv3: Harnessing integrated attention and transfer learning for next-generation skin lesion detection,” in 2024 IEEE International Conference on Computing, Applications and Systems (COMPAS), IEEE, 2024, pp. 1–6.

[2024] M. R. Oishe, S. M. Hasan, and M. F. Zibran, “Breaking the mold: Vit-cnn fusion for enhanced glaucoma prediction in oct images,” in International Conference on Artificial Intelligence and Soft Computing, Springer, 2024, pp. 326–344.

[2024] M. Rahman, S. Agarwala, A. Y. Srizon, et al., “A cost-effective approach to bengali handwritten character recognition with custom convolutional neural network,” in 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON), IEEE, 2024, pp. 894–899.

[2024] T. Rahman, M. F. Faruk, M.N. Khansur, et al., “3d cnn with attention modules for enhanced covid-19 and pneumonia screening from ct scans,” in 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON), IEEE, 2024, pp. 613–618.

[2024] B. Roy, M. F. Faruk, M. N. Islam, et al., “A cutting-edge ensemble of vision transformer and resnet101v2 based transfer learning for the precise classification of leukemia sub-types from peripheral blood smear images,” in 2024 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT), IEEE, 2024, pp. 49–54.

[2024] P. Roy, A. H. Efat, S. M. Hasan, et al., “Multi-scale feature fusion framework based on attention integrated customized densenet201 architecture for multi-class skin lesion detection,” in 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON), IEEE, 2024, pp. 496–501.

[2024] S. Samira, M. F. Faruk, M.N. Islam, et al., “Enhancing gastrointestinal diagnosis: Cbam-integrated cnn for high-precision multi-class anatomical landmark identification,” in 2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE), IEEE, 2024, pp. 1–6.

[2023] F. Akter, S. Shakib-Ul-Shadat, M. R. Hossain, S. M. Hasan, and S. Datto, “The usage of a fast power switching law in the design of a global integral terminal sliding mode controller for step up converter in application of fuel cell,” in 2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI), IEEE, 2023, pp. 1–5.

[2023] S. S. Akter, M. R. Hossain, S. M. Hasan, et al., “Decoding smart grid equilibrium: Insights from machine learning models,” in 2023 10th IEEE International Conference on Power Systems (ICPS), IEEE, 2023, pp. 1–6.

[2023] A. Barai, M. F. Faruk, S. M. Shuvo, A. Y. Srizon, S. M. Hasan, and A. Sayeed, “A late fusion deep cnn model for the classification of brain tumors from multi-parametric mri images,” in 2023 International Conference on Next-Generation Computing, IoT and Machine Learning (NCIM), IEEE, 2023, pp. 1–6.

[2023] A. Basak, F. Akter, M. R. Hossain, et al., “A novel cnn-bilstm fusion model for robust age estimation from facial images,” in 2023 26th International Conference on Computer and Information Technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] S. Datta, S. M. Hasan, M. F. Faruk, et al., “Improved diabetes prediction with reduced feature sets: Evaluating feature selection techniques in machine learning,” in 2023 International conference on information and communication technology for sustainable development (ICICT4SD), IEEE, 2023, pp. 104–108.

[2023] S. Datta, S. M. Hasan, M. Mitu, M. F. Taraque,N. Jannat, and A. H. Efat, “Hyperparameter-tuned machine learning models for complex medical datasets classification,” in 2023 International conference on electrical, computer and communication engineering (ECCE), IEEE, 2023, pp. 1–6.

[2023] S. Emon, M. R. Hossain, S. M. Hasan, et al., “Prediction of medical insurance costs: A shap-enhanced predictive analysis for transparency and interpretability,” in 2023 26th International Conference on Computer and Information Technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] Z. Ferdusi, F. Akter, A. S. Jewel, et al., “Designing a backstepping integral terminal sliding mode controller for pemfc system employing a dc-dc boost converter,” in 2023 10th IEEE International Conference on Power Systems (ICPS), IEEE, 2023, pp. 1-5.

[2023] M. Hadee, F. Akter, M. R. Hossain, S. M. Hasan, S. S. Akter, and S. Datto, “Lqr based current controller for improved power quality of grid-tied pv systems,” in 2023 10th IEEE International Conference on Power Systems (ICPS), IEEE, 2023, pp. 1–6.

[2023] N. Haque, A. H. Efat, S. M. Hasan, N. Jannat, M. Oishe, and M. Mitu, “Revolutionizing pest detection for sustainable agriculture: A transfer learning fusion network with attention-triplet and multi-layer ensemble,” in 2023 26th international conference on computer and information technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] R. Haque, S. M. Hasan, A. Y. Srizon, et al., “Evaluating the efficacy of feature selection methods in cardiovascular disease prediction with machine learning,” in 2023 6th International Conference on Electrical Information and Communication Technology (EICT), IEEE, 2023, pp. 1–6.

[2023] S. M. Hasan, M. Al Mamun, M. F. Faruk, and A. Y. Srizon, “Ensemble of deep convolutional neural networks for multi-class skin lesion recognition using soft attention,” in 2023 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD), IEEE, 2023, pp. 65–69.

[2023] S. M. Hasan, A.Mamun, and A. Y. Srizon, “Enhancing multi-class skin lesion classification with modified efficientnets: Advancing early detection of skin cancer,” in 2023 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD), IEEE, 2023, pp. 94–98.

[2023] M. S. Hossain, M. F. Faruk, A. Y. Srizon, et al., “A customized 3d cnn integrated with convolutional block attention module for precise diagnosis of covid-19 and pneumonia from ct scan images,” in 2023 26th International Conference on Computer and Information Technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] M. S. Hossain, M. R. Hossain, S. M. Hasan, et al., “Leveraging ai-driven strategies to mitigate employee turnover in commercial industries,” in 2023 26th International Conference on Computer and Information Technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] F. Islam, M. F. Faruk, S. M. Hasan, et al., “An investigation of hyperparameters optimization and feature reduction techniques: Predicting airline passenger satisfaction using machine learning models,” in 2023 26th International Conference on Computer and Information Technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] M. M. Islam, S. M.Hasan, M. R.Hossain, et al., “Channel attention-guided lightweight cnn meets extreme learning machine: Multi-class crop leaf disease classification with explainable ai,” in 2023 26th International Conference on Computer and Information Technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] M. M. Islam, T. Jubaer, A. Y. Srizon, et al., “Navigating bengali linguistics: Insights from machine and deep learning perspectives for categorization of sentences,” in 2023 26th International Conference on Computer and Information Technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] M. N. Islam, M. AlMamun, M. F. Faruk, A. Y. Srizon, S. M. Hasan, and B. Roy, “Spatial attention-guided deep learning for accurate kidney disease classification in ct scans,” in 2023 26th International Conference on Computer and Information Technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] R. Islam, M. R. Hossain, S. M. Hasan, et al., “Enhanced brain tumor classification using squeeze and excitation attention-guided modified efficientnetb2 architecture,” in 2023 26th International Conference on Computer and Information Technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] N. Jannat, S. M. Hasan, A. H. Efat, et al., “Stacking ensemble technique for multiple medical  datasets classification: A generalized prediction model,” in 2023 International Conference on Electrical, Computer and Communication Engineering (ECCE), IEEE, 2023, pp. 1–6.

[2023] N. Jannat, S. M. Hasan, A. Y. Srizon, et al., “Efficient detection of crop leaf diseases: A lightweight convolutional neural network approach for enhanced agricultural productivity,” in 2023 International conference on information and communication technology for sustainable development (ICICT4SD), IEEE, 2023, pp. 99– 103.

[2023] T. S. Joy, A. H. Efat, S. M. Hasan, et al., “Attention trinity net and densenet fusion: Revolutionizing american sign language recognition for inclusive communication,” in 2023 26th international conference on computer and information technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] M. Karim, F. Akter, M. R. Hossain, S. M. Hasan, and S. Datto, “An artificial intelligent system for driving content engagement in video sharing platform,” in 2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI), IEEE, 2023, pp. 1–6.

[2023] M. Mitu, S. M. Hasan, A. H. Efat, M. F. Taraque, N. Jannat, and M. Oishe, “An explainable machine learning framework for multiple medical datasets classification,” in 2023 International Conference on Next- Generation Computing, IoT and Machine Learning (NCIM), IEEE, 2023, pp. 1–6.

[2023] A. Montashir Fahim, A. H. Efat, S. Mahedy Hasan, M. R. Oishe, N. Jannat, and M. Mitu, “Tri focus net: A cnn-based model with integrated attention modules for pest and insect detection in agriculture,” in International conference on trends in electronics and health informatics, Springer, 2023, pp. 225–240.

[2023] S. F. Rabbi, M. Al Mamun, M. F. Faruk, S. M. Hasan, and A. Y. Srizon, “A multi-branch and attention based cnn architecture for the classification of retinal diseases from oct images,” in 2023 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD), IEEE, 2023, pp. 36–40.

[2023] T. I. Sajon, M. Chowdhury, A. Y. Srizon, et al., “Recognition of leukemia sub-types using transfer learning and extraction of distinguishable features using an effective machine learning approach,” in 2023 inter- national conference on electrical, computer and communication engineering (ECCE), IEEE, 2023, pp. 1–6.

[2023] T. I. Sajon, B. Roy, M. F. Faruk, et al., “Attention mechanism-enhanced deep cnn architecture for precise multi-class leukemia classification,” in International Conference on Big Data, IoT and Machine Learning, Springer, 2023, pp. 349–361.

[2023] S. Sakib, M. R. Hossain, S. M. Hasan, et al., “Predictive analytics in agriculture: Unraveling the determinants of crop yield with machine learning,” in 2023 26th International Conference on Computer and Information Technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] S. Shafin, A. H. Efat, S. M. Hasan, et al., “Skin lesion classification through sequential triple attention densenet: Diverse utilization of the combination of attention modules,” in 2023 26th International conference on computer and information technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] M. M. U. S. Shakin, F. Akter, S. M. Hasan, et al., “Squeeze and excitation attention meets modified effi-cientnetb0 architecture: Multi-class brain tumor classification using explainable artificial intelligence,” in 2023 26th International Conference on Computer and Information Technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] S. M. Shuvo, M. F. Faruk, A. Y. Srizon, et al., “Multi-class brain tumor classification with densenet-based deep learning features and ensemble of machine learning approaches,” in  International Conference on Big Data, IoT and Machine Learning, Springer, 2023, pp. 559–573.

[2023] S. Sikder, A. H. Efat, S. M. Hasan, et al., “A triple-level ensemble-based brain tumor classification using dense-resnet in association with three attention mechanisms,” in 2023 26th International conference on computer and information technology (ICCIT), IEEE, 2023, pp. 1–6.

[2023] A. Y. Srizon, A. Sarker, M. Al Mamun, M. F. Faruk, and S. M. Hasan, “Enhancing waste  categorization using ensemble of transfer learning and light-weight convolutional neural network,” in 2023 International Conference on Next-Generation Computing, IoT and Machine Learning (NCIM), IEEE, 2023, pp. 1–6.

[2022] A. H. Efat, S. M. Hasant, N. Jannat, et al., “Inquisition of the support vector machine classifier in association with hyper-parameter tuning: A disease prognostication model,” in 2022 4th international conference on electrical, computer & telecommunication engineering (ICECTE), IEEE, 2022, pp. 131–134.

[2022] M. F. F. Isty, S. M. Hasan, and M. S. I. Shopnil, “Performance analysis of hybrid deep learning models in sarcasm classification,” in 2022 25th International Conference on Computer and Information Technology (ICCIT), IEEE, 2022, pp. 1092–1097.

[2022] M. Rahman, M. Hossain, and S. Hasan, “The development of an image searching method by a content based image retrieval system,” in 2022 International Conference on Recent Progresses in Science, Engineering and Technology (ICRPSET), IEEE, 2022, pp. 1–5.

[2022] M. S. I. Shopnil, S. M. Hasan, M. A. Y. Srizon, and M. F. Faruk, “Post-pandemic sentiment analysis based on twitter data using deep learning,” in 2022 25th International Conference on Computer and Information Technology (ICCIT), IEEE, 2022, pp. 704–709.

[2022] A. Y. Srizon, S. M. Hasan, M. F. Faruk, A. Sayeed, and M. A. Hossain, “Human activity recognition utilizing ensemble of transfer-learned attention networks and a low-cost convolutional neural architecture,” in 2022 25th International Conference on Computer and Information Technology (ICCIT), IEEE, 2022, pp. 943– 948.

[2022] M. F. Taraque, S. M. Hasan, N. Jannat, et al., “Early stage prediction of autism spectrum disorder: Analyzing different hyperparameter tuned machine learning classifier,” in 2022 4th International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE), IEEE, 2022, pp. 1–4.

[2021] A. I. Champa, M. F. Rabbi, S. M. Hasan, A. Zaman, and M. H. Kabir, “Tree-based classifier for hyperspectral image classification via hybrid technique of feature reduction,” in 2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD), IEEE, 2021, pp. 115– 119.

[2021] M. Fazle Rabbi, S. Mahedy Hasan, A. I. Champa, M. Rifat Hossain, and M. Asif Zaman, “A convolutional neural network model for screening covid-19 patients based on ct scan images,” in Proceedings of the International Conference on Big Data, IoT, and Machine Learning: BIM 2021, Springer, 2021, pp. 141–151.

[2021] S. M. Hasan, M. F. Rabbi, A. I. Champa, and M. A. Zaman, “A comparative study of classification approaches for covid-19 prediction,” in 2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD), IEEE, 2021, pp. 105–109.

[2021] M. F. Rabbi, S. M. Hasan, A. I. Champa, and M. A. Zaman, “A convolutional neural network model for early-stage detection of autism spectrum disorder,” in 2021 international conference on information and communication technology for sustainable development (icict4sd), IEEE, 2021, pp. 110–114.

[2020] A. I. Champa, S. M. Hasan, M. A. Rahman, and M. F. Rabbi, “Hybrid technique for classification of hyperspectral image using quadratic mutual information,” in 2020 IEEE Region 10 Symposium (TENSYMP), IEEE, 2020, pp. 933–936.

[2020] S. M. Hasan, M. F. Rabbi, A. I. Champa, and M. A. Zaman, “A machine learning-based model for early stage detection of diabetes,” in 2020 23rd International Conference on Computer and Information Technology (ICCIT), IEEE, 2020, pp. 1–6.

[2020] S. M. Hasan, M. F. Rabbi, A. I. Champa, and M. A. Zaman, “An effective diabetes prediction system using machine learning techniques,” in 2020 2nd International Conference on Advanced Information and Communication Technology (ICAICT), IEEE, 2020, pp. 23–28.

[2020] M. F. Rabbi, S. M. Hasan, A. I. Champa, M. AsifZaman, and M. K. Hasan, “Prediction of liver disorders using machine learning algorithms: A comparative study,” in 2020 2nd International Conference on Advanced Information and Communication Technology (ICAICT), IEEE, 2020, pp. 111–116.

[2020] S. Hasan, M. Mamun, M. Uddin, and M. Hossain, “Comparative analysis of classification approaches for heart disease prediction,” in 2018 International Conference on Computer, Communication, Chemical, Material and Electronic Engineering (IC4ME2), IEEE, 2018, pp. 1–4.