Kazi Tanvir

@vit.ac.in

Department of Mathematics, School of Advanced Sciences,
Vellore Institute of Technology

Kazi Tanvir


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https://researchid.co/ktanvir

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence, Computer Vision and Pattern Recognition, Multidisciplinary, Information Systems
39

Scopus Publications

174

Scholar Citations

8

Scholar h-index

6

Scholar i10-index

Scopus Publications

  • FRF-HHO: Early ovarian cancer prediction using explainable fuzzy random forest optimized by Harris Hawks algorithm
    K.M. Yeaser Arafat, Ahmed Hossain, Mushfika Ikfat, Md. Areful Amin, Kazi Tanvir, Dipta Gomes, Mahfujur Rahman
    Advances in Biomarker Sciences and Technology, 2026
    Ovarian cancer remains one of the most lethal gynecological malignancies, largely due to delayed diagnosis and the absence of reliable early screening tools. This study proposes an interpretable machine learning framework that integrates Fuzzy Random Forest (FRF) with Harris Hawks Optimization (HHO) for early ovarian cancer prediction using routine clinical data. The analysis was conducted on a publicly available dataset comprising 349 patient records with 51 clinical and biochemical features. To mitigate overfitting and data leakage, Recursive Feature Elimination with Cross-Validation (RFECV), preprocessing, and SMOTE–Tomek balancing were applied exclusively within the training data. A total of 31 relevant biomarkers were selected for model development. The HHO-optimized FRF achieved an accuracy of 94.12%, precision of 91.43%, recall of 96.07%, and an F1-score of 93.69%, outperforming several baseline ensemble and gradient boosting models evaluated under identical experimental conditions. Model interpretability was enhanced through SHAP and LIME analyses, which consistently identified AFP, HE4, CA125, and Age as influential predictors, aligning with established clinical knowledge. The high recall indicates strong sensitivity to cancer cases, an essential requirement for diagnostic support. Despite encouraging performance, the study is limited by its moderate sample size and a retrospective design. Consequently, the findings should be interpreted as preliminary. Future work will focus on validation using larger, multi-center cohorts and prospective studies to assess generalizability and clinical scalability. • Hybrid FRF-HHO model achieved 94.12% accuracy and 96.07% recall for early ovarian cancer prediction. • RFECV selected 31 key clinical biomarkers, improving diagnostic precision and reducing dimensionality. • Explainable AI (SHAP and LIME) revealed AFP, HE4, CA125, and Age as dominant diagnostic indicators. • Model demonstrated superior interpretability and reliability, outperforming existing ML frameworks statistically (p < 0.05).
  • SSC-BanglaTutor: A curriculum-aligned Bengali dataset for intelligent tutoring systems
    Eshraque Jabid Ifti, Fihab Ifty, Mehadi Hasan, Rahul Chandra Shil, Utshab Kumar Saha, Kazi Tanvir, Mahfujur Rahman, Dipta Gomes
    Data in Brief, 2026
    This dataset presents a Bengali-language dataset designed to fine-tune AI powered hint-based tutoring systems for the Secondary School Certificate (SSC) science curriculum in Bangladesh. This data includes 11,286 hint-based question-answer entries, comprising 4859 questions from Biology covering 14 chapters, 3034 from Chemistry across 12 chapters, and 3393 from Physics spanning 14 chapters. All items were created manually using government-issued textbooks, SSC focused study materials, and past exam question banks. Each question is paired with candidate answers containing one correct option and several closely related but incorrect options to help measure the effectiveness of the hints. A convergence score is attached to each entry, estimating how far a student may need to go through the hints to answer correctly. These features support personalized feedback and offer meaningful insight into the students' learning progress. The dataset is encoded in UTF-8, with some English terms retained for scientific precision and consistency with source materials. This makes it accessible to native learners while remaining valuable for low-resource Natural Language Processing (NLP) applications. By emphasizing curriculum alignment, ranked hinting, and learner modeling, the dataset provides a strong foundation for fine-tuning large language models (LLMs) and developing intelligent tutoring systems that are both linguistically inclusive and educationally effective.
  • A Comprehensive Study on the Ethical Perspective of Integration of Agentic AI for Autonomous Vehicles
    Mirza Asif Mahmud, Mahfujur Rahman, Dipta Gomes, Kazi Tanvir, Md. Reazul Islam
    Agentic AI for Autonomous Vehicles Safety Reliability Law and Ethics, 2026
    This chapter explores the ethical integration of Agentic AI into autonomous vehicles, detailing a technical architecture that embeds ethical considerations across goal setting, memory, human oversight, transparency, and robustness. It highlights how V2X connectivity transforms AVs into collaborative agents within intelligent ecosystems. The chapter also presents evaluation frameworks and metrics to measure safety, fairness, and public trust, ensuring autonomous driving aligns with societal values and legal standards.
  • ViTBiT-PoxNet: An Explainable Hybrid Deep Learning Framework for Enhanced Early-Stage Monkeypox Classification
    Md Sadi Al Huda, Tahmid Enam Shrestha, Kazi Tanvir, Rafat Ahmed, Md. Asraf Ali, Touhid Bhuiyan
    Lecture Notes in Networks and Systems, 2026
  • Harnessing AI for Seamless E-Collaboration in Healthcare Through Building Smarter, Connected, and PatientCentric Systems
    Noboranjan Dey, Mahfujur Rahman, Shaikat Das Joy, Kazi Tanvir, Rahul Biswas, Dipta Gomes
    Strengthening E Collaboration in Healthcare Through AI, 2026
    This chapter explores the transformative role of Artificial Intelligence (AI) in healthcare, focusing on its evolution from experimental technology to a key driver of digital transformation and e-collaboration. It examines how advances in machine learning, natural language processing, robotics, blockchain, and Internet of Medical Things (IoMT) have enabled AI-powered tools to enhance patient care, clinical decision-making, and operational efficiency. The chapter highlights AI's impact across telemedicine, remote diagnostics, multidisciplinary collaboration, and personalized medicine, emphasizing how AI complements human expertise by automating routine tasks and enabling real-time data sharing. It also discusses challenges related to ethics, privacy, and regulation, while outlining future trends and global efforts to standardize AI adoption in healthcare.
  • Transformer-Based and Probabilistic Approaches for Topic Modeling in News Article Analysis
    Rafin Abrar Rono, Md. Sayem Kabir, Sadman Samir Rafith, Md. Bakibillah Rahat, Tasnim Sultana Sintheia, Kazi Tanvir
    Lecture Notes in Networks and Systems, 2026
  • Vision Language Models in Healthcare Through a Multimodal Approach to Medical Imaging and Clinical Applications
    Kazi Tanvir, Rahul Biswas, Dipta Gomes, Mahfujur Rahman, Noboranjan Dey, Md. Reazul Islam
    Vision Language Models for Next Generation Healthcare, 2026
    This chapter explores the emerging role of Vision Language Models (VLMs) in healthcare, focusing on their ability to integrate visual and textual data to improve medical imaging analysis and clinical decision-making. It examines the key components of VLMs, including vision and language models, their fusion techniques, and their applications in tasks like disease detection, report generation, and visual question answering. The chapter also addresses challenges such as data scarcity, privacy concerns, and model interpretability. Additionally, it highlights future directions for enhancing model generalization, improving explainability, and ensuring seamless integration into clinical workflows, while emphasizing the importance of ethical considerations and real-world validation for safe deployment in healthcare environments.
  • Synthetic Healthcare Data in Generation, Validation, and Integration for Ethical and Scalable Health Innovation
    Shaikat Das Joy, Noboranjan Dey, Md. Reazul Islam, Mirza Asif Mahmud, Mahfujur Rahman, Kazi Tanvir, Dipta Gomes
    Advances in Synthetic Healthcare Data Opportunities Challenges and Emerging Trends, 2026
    Synthetic healthcare data offers a transformative solution to the privacy and accessibility constraints of real patient data. This chapter comprehensively examines its generation, from traditional statistical methods to advanced AI like GANs, VAEs, and Transformers. It explores critical applications in clinical trial simulation, medical imaging, and AI training. The analysis extends beyond technology to address pivotal barriers: ethical concerns of bias, evolving GDPR/HIPAA regulations, validation challenges, and interoperability with systems like HL7 FHIR. It concludes that responsible adoption hinges on merging technical rigor with ethical governance and cross-disciplinary collaboration to build trustworthy, innovative digital health ecosystems.
  • An explainable ensemble learning framework for ovarian cancer classification using blood biomarkers
    Kazi Tanvir, Md. Sayem Kabir, Kazi Tasnim Hena, Tasnim Sultana Sintheia, Shanzida Zaman Shimu, Dipta Gomes, Mahfujur Rahman, Mirza Asif Mahmud
    Informatics and Health, 2026
    Background Ovarian cancer remains one of the most lethal gynecological malignancies, largely due to delayed diagnosis and the limited sensitivity of conventional screening approaches. Methods This study proposes an interpretable machine learning framework for the binary classification of ovarian cancer and benign ovarian tumors using routine blood biomarker data. A soft voting ensemble combining Histogram-Based Gradient Boosting and K-Nearest Neighbors was developed to capture complementary global and local data patterns. Class imbalance was mitigated using the ROSE resampling technique, while LASSO-based embedded feature selection improved model robustness and generalization. Model transparency was ensured through a comprehensive explainable AI pipeline incorporating SHAP, LIME, anchor rules, ELI5, Partial Dependence Plots, and surrogate decision trees. Findings The proposed ensemble consistently outperformed eleven benchmark classifiers across multiple resampling strategies, achieving a maximum accuracy and F1-score of 98.61Interpretation Integrating ensemble learning with multi-level explainability yields a highly accurate, reliable, and clinically interpretable diagnostic tool, supporting its potential adoption in real-world ovarian cancer screening and decision-support systems.
  • A Framework for Robust and Interpretable Yield-Risk Classification Using Country-Year-Crop Data (X- AMLF)
    Sk Muktadir Hossain, Sharif Eime Akhter, Ayswarjo Sarkar, Kazi Samia Mostofa, Md Sadiqur Rahman, Dipta Gomes, Mahfujur Rahman, Kazi Tanvir
    AI for Climate Governance Agriculture and Earth Systems, 2026
    This study introduces the Explainable Agro-Intelligence Machine Learning Framework (X-AMLF), which is a structured evaluation framework for yield risk classification in agriculture using aggregated country-year-crop data. A harmonised dataset was created by combining data on crop yield, annual average temperature, rainfall, pesticide use, crop identity, and country indicators to create 28,242 complete observations on the yield of 101 countries (1990–2016) for 10 major crops. Multiple classification models were evaluated, such as linear baselines and tree-based ensembles, and hyperparameters were optimised with Optuna to investigate variations in prediction and error behaviour. Under random splitting, ensemble models were able to get very high scores (e.g. Random forest F1 ≈ 0.976), but under a stricter evaluation, performance dropped. With country-holdout validation, the best-performing models had F1 ≈ 0.843, attenuation of performance when tested on unseen regions.
  • IoMT Architecture for Healthcare: Integration, Security, and Real-Time Decision Support
    Md. Reazul Islam, Mirza Asif Asif Mahmud, Kazi Tanvir, Shaikat Das Joy, Mahfujur Rahman, Noboranjan Dey, Dipta Gomes
    Robotics and Iot Synergy in Next Generation Healthcare, 2025
  • Efficient Disease and Pests Detection in Cotton Leaves Using NASBiT with Enhanced XAI visualization
    Md. Sayem Kabir, Sharia Arfin Tanim, Kazi Tanvir, Kamruddin Nur, Mohamed Haq
    Icca 2024 3rd International Conference on Computing Advancements 2024, 2025
  • Potato Diseases detection using Inception-BiT with Explainable AI
    Md. Sayem Kabir, Md Nure Alam Nadim, Sharia Arfin Tanim, Tasnim Sultana Sintheia, Kazi Tanvir, Muhibul Haque Bhuyan
    Icca 2024 3rd International Conference on Computing Advancements 2024, 2025
  • Enhancing Poultry Disease Classification Using Fecal Image: A Fusion Approach
    Md Sadi Al Huda, Adety Sarkar, Kazi Tanvir, Md Asraf Ali, Dip Nandi, Mohamed Haq
    Icca 2024 3rd International Conference on Computing Advancements 2024, 2025
  • AI-driven insights into revolutionizing poultry farming with behavioral monitoring and ethical management
    Md. Sayem Kabir, Tasnim Sultana Sintheia, Kazi Tanvir, Dipta Justin Gomes
    Intelligent Internet of Everything for Automated and Sustainable Farming, 2025
  • Smart agriculture using advancing tea leaf quality assessment with deep learning
    Md. Sayem Kabir, Mohammad Ariyan Pathan, Kazi Tanvir, Dipta Justin Gomes
    Intelligent Internet of Everything for Automated and Sustainable Farming, 2025
  • CNNRF-Ensemble: A Multifaced Approach For Predicting White Spot Syndrome Virus In Shrimp Farming
    Kazi Tanvir, Sadi Al Huda, Shaiful Ajam Opee, Sayem Kabir, Asraf Ali, Touhid Bhuiyan
    International Conference on Robotics Electrical and Signal Processing Techniques, 2025
  • PT-TwinDCNN: A Dual-Stream Deep Learning Model for Arsenic-Induced Skin Lesions Classification
    Md. Sayem Kabir, Kazi Tanvir, Tasnim Sultana Sintheia, Mian Mohammad Rassel, K. M. Tahsin Kabir, Md. Fahim Kabir Chowdhury
    2025 IEEE International Conference on Quantum Photonics Artificial Intelligence and Networking Qpain 2025, 2025
  • Enhanced Java Plum Leaf Disease Classification Using ShuffleNetV2 and GSA-Tuned AdaBoost
    Md. Fahim Kabir Chowdhury, Md. Sayem Kabir, Sadman Samir Rafith, Kazi Tanvir, Farzana Nazera, Dipta Gomes
    2025 IEEE 2nd International Conference on Computing Applications and Systems Compas 2025, 2025
  • Explainability in Orange Disease Detection through a Res-Inception Framework Integrating Deep Learning Techniques
    Kazi Tanvir, Sharia Arfin Tanim, Md. Sayem kabir, K.M. Tahsin Kabir, Mian Mohammad Rassel, Md. Faruk Abdullah al Sohan
    Procedia Computer Science, 2025
  • PCNN-Based Grape Leaf Disease Detection Using MobileNetV2 and ViT with XAI
    Kazi Tanvir, Ritik Sharma, Md. Sayem Kabir, Tasnim Sultana Sintheia, Soumya Basu, Soumik Banerjee
    Lecture Notes in Networks and Systems, 2025
  • Hybrid Vision Transformer Naive Bayes Model for Mosquito Species Recognition with Virus Colony Search Optimization
    Farzana Nazera, Kazi Tanvir, Md. Sayem Kabir, MD. Shakil Hasan, Kazi Tasnim Hena, Dipta Gomes
    2025 IEEE International Conference on Quantum Photonics Artificial Intelligence and Networking Qpain 2025, 2025
  • Automated Classification of Husk Species Using DenseNet121 and Vision Transformer
    Dipta Gomes, Kazi Tanvir, Md. Sayem Kabir, Tasnim Sultana Sintheia, Sadman Samir Rafith, Mohammad Ariyan Pathan
    Communications in Computer and Information Science, 2025
  • Automated Bladder Tissue Classification Using ViTXception with Explainable AI
    Md. Sayem Kabir, Mohammad Ariyan Pathan, Paul Tamal, Laboni Somoddar, Kazi Tanvir, Dipta Gomes
    2025 IEEE 7th International Conference on Sustainable Technologies for Industry 5 0 Sti 2025, 2025
  • Enhancing Lemon quality detection using Efficient-MobileNet with Explainable AI
    Md Rakibuzzman, Saif Mostasir Rohan, Tasnim Sultana Sintheia, Md. Sayem Kabir, Mian Mohammad Rassel, Kazi Tanvir
    2025 International Conference on Electrical Computer and Communication Engineering Ecce 2025, 2025
  • Efficient Chicken Audio Classification Using Swin Transformer Features and Harmony-Optimized Random Forest
    Md. Sayem Kabir, Kazi Tanvir, Sadman Samir Rafith, Mohammad Ariyan Pathan, Md Sadi Al Huda, Touhid Bhuiyan
    Communications in Computer and Information Science, 2025
  • Explainable Detection and Analysis of Cauliflower Leaf Diseases
    Sharia Arfin Tanim, Rubaba Binte Rahman, Kazi Tanvir, Md. Sayem Kabir, Tasnim Sultana Sintheia, Md Saef Ullah Miah
    Lecture Notes in Computer Science, 2025
  • Apple Leaf Disease Classification Using Big Transfer with Modified Z-Score
    Kazi Tanvir, Damodharan R, Lisha H V, Venkataramana B
    2024 4th International Conference on Artificial Intelligence and Signal Processing Aisp 2024, 2024
  • Enhancing Corn Leaf Disease Identification with DenseViT Model
    Kazi Tanvir, H V Lisha, R Damodharan, Karthikeyan Sivashanmugam
    2024 3rd International Conference on Artificial Intelligence for Internet of Things Aiiot 2024, 2024
  • Elevating Mango Leaf Disease Classification Utilizing Dense ViT
    Farzana Nazera, Abdullah N A Nadim, Subrato Kumar Dey, Kazi Tanvir, Md. Sayem Kabir
    Proceedings 3rd International Conference on Advances in Computing Communication and Applied Informatics Accai 2024, 2024
  • Forest Fire Detection Using Ensemble Deep Learning Model With XAi
    Kazi Tanvir, Md. Sayem Kabir, Zahid Hasan Anik, Md. Rakib Hasan, MD. Tanbin Tushar, Rubaba Binte Rahman
    2024 IEEE Conference on Computing Applications and Systems Compas 2024, 2024
  • Single-Level Fusion for Enhancing Meat Quality Classification with Explainable AI
    Sharia Arfin Tanim, Tahmid Enam Shrestha, Kazi Tanvir, Md. Sayem Kabir, M. F. Mridha, Mohamed Kaisarul Haq
    2024 IEEE Conference on Computing Applications and Systems Compas 2024, 2024
  • ResViT: An Integrated Approach Using ResNet50v2 and Vision Transformer for Enhanced Bangla Handwritten Character Recognition
    Kazi Tanvir, Md Sadi Al Huda, Md. Sayem Kabir, Rezwan Obayed, Md. Fahim Attef, Md. Asraf Ali
    2nd International Conference on Information and Communication Technology Icict 2024, 2024
  • Enhancing Monkeypox Diagnostics: Exploring the Potential of EfficientNet and Big Transfer
    Sharia Arfin Tanim, Kazi Tanvir, Al Rafi Arnob, Md. Hasibur Rahman, Tasmia Binte Munir Maisha, Kamruddin Nur
    Journal of Image and Graphics United Kingdom, 2024
  • Enhancing Banana Leaf Spot Disease Classification using Dense Mobilenet V2
    Mohamed Kaisarul Haq, Kazi Tanvir, Md. Sayem Kabir, Nure Saba Binte Alam, Subrato Kumar Dey, Valliappan Raju
    Proceedings 3rd International Conference on Advances in Computing Communication and Applied Informatics Accai 2024, 2024
  • Enhancing Watermelon Diseases Detection using Dense-EfficientNet and Explainable AI
    Jahidul Islam, Md. Sayem Kabir, K. M Tahsin Kabir, Tasnim Sultana Sintheia, Kazi Tanvir, Dipta Gomes
    2024 27th International Conference on Computer and Information Technology Iccit 2024 Proceedings, 2024
  • AI-Driven Hybrid Approach to Optimizing Dragonfruit Quality Assessment for Sustainable Agriculture
    Md. Fahim Kabir Chowdhury, Md. Sayem Kabir, Saif Mostasir Rohan, K. M. Tahsin Kabir, Kazi Tanvir, Md. Mahmudur Rahman
    2024 27th International Conference on Computer and Information Technology Iccit 2024 Proceedings, 2024
  • Enhancing Coconut Tree Diseases Detection with Efficient-NASNet using xAI
    Md Rakibuzzman, Md Nure Alam Nadim, Md. Sayem Kabir, Mian Mohammad Rassel, Kazi Tanvir, Md. Faruk Abdullah Al Sohan
    13th International Conference on Electrical and Computer Engineering Icece 2024, 2024
  • Advancing Monkeypox Diagnosis: A Novel Approach using a Custom Neural Networks
    Md. Sayem Kabir, Md Sadi Al Huda, Kazi Tanvir, Fariha Tahseen Karim, Md Musfikur Rahman Parvej, Shaif Ahamed Tamim, Md. Asraf Ali
    2nd International Conference on Information and Communication Technology Icict 2024, 2024

RECENT SCHOLAR PUBLICATIONS

  • An explainable ensemble learning framework for ovarian cancer classification using blood biomarkers
    K Tanvir, MS Kabir, KT Hena, TS Sintheia, SZ Shimu, D Gomes, ...
    Informatics and Health , 2026
    2026
  • ViTBiT-PoxNet: An Explainable Hybrid Deep Learning Framework for Enhanced
    MS Al Huda¹, TE Shrestha, K Tanvir, R Ahmed, MA Ali, T Bhuiyan
    Proceedings of Fifth International Conference on Computing and Communication … , 2026
    2026
  • SSC-BanglaTutor: A curriculum-aligned Bengali dataset for intelligent tutoring systems
    EJ Ifti, F Ifty, M Hasan, RC Shil, UK Saha, K Tanvir, M Rahman, D Gomes
    Data in Brief, 112597 , 2026
    2026
  • Approaches for Topic Modeling in News Article Analysis
    MB Rahat, TS Sintheia, K Tanvir
    Proceedings of the 3rd International Conference on Big Data, IoT and Machine … , 2026
    2026
  • FRF-HHO: Early ovarian cancer prediction using explainable fuzzy random forest optimized by Harris Hawks algorithm
    KMY Arafat, A Hossain, M Ikfat, MA Amin, K Tanvir, D Gomes, M Rahman
    Advances in Biomarker Sciences and Technology , 2026
    2026
  • A Comprehensive Study on the Ethical Perspective of Integration of Agentic AI for Autonomous Vehicles
    MA Mahmud, M Rahman, D Gomes, K Tanvir, MR Islam
    Agentic AI for Autonomous Vehicles: Safety, Reliability, Law, and Ethics … , 2026
    2026
  • Vision Language Models in Healthcare Through a Multimodal Approach to Medical Imaging and Clinical Applications
    K Tanvir, R Biswas, D Gomes, M Rahman, N Dey, MR Islam
    Vision Language Models for Next-Generation Healthcare, 259-292 , 2026
    2026
  • From Computational Screening to In Vitro Validation: Exploring Antimicrobial Peptides against Pseudomonas aeruginosa
    D CHATTERJEE, I Biswas, S Mittal, S Routh, K Tanvir, K Sivashanmugam, ...
    Frontiers in Microbiology 17, 1796090 , 2026
    2026
  • Harnessing AI for Seamless E-Collaboration in Healthcare Through Building Smarter, Connected, and Patient-Centric Systems
    N Dey, M Rahman, SD Joy, K Tanvir, R Biswas, D Gomes
    Strengthening E-Collaboration in Healthcare Through AI, 1-48 , 2026
    2026
  • A Framework for Robust and Interpretable Yield-Risk Classification Using Country–Year–Crop Data (X-AMLF)
    SM Hossain, SE Akhter, A Sarkar, KS Mostofa, MS Rahman, D Gomes, ...
    AI for Climate Governance, Agriculture, and Earth Systems, 237-292 , 2026
    2026
  • Automated Classification of Husk Species Using DenseNet121 and Vision
    D Gomes, K Tanvir, MS Kabir¹
    Data Science, AI and Applications: First International Conference, ICDSAIA … , 2026
    2026
  • Synthetic Healthcare Data in Generation, Validation, and Integration for Ethical and Scalable Health Innovation
    SD Joy, N Dey, MR Islam, MA Mahmud, M Rahman, K Tanvir, D Gomes
    Advances in Synthetic Healthcare Data: Opportunities, Challenges, and … , 2026
    2026
  • IoMT Architecture for Healthcare: Integration, Security, and Real-Time Decision Support
    MR Islam, MAA Mahmud, K Tanvir, SD Joy, M Rahman, N Dey, D Gomes
    Robotics and IoT Synergy in Next-Generation Healthcare, 305-340 , 2026
    2026
    Citations: 1
  • Explainable Breast Cancer Diagnosis with Vision Transformers and ACOR-Optimized Decision Trees
    SS Rafith, SM Rohan, MS Kabir, K Tanvir, D Gomes, M Rahman
    2025 28th International Conference on Computer and Information Technology … , 2025
    2025
  • XGception: Unveiling Mosquito Larvae Patterns with XAI
    SM Rohan, SS Rafith, MS Kabir, MH Pranto, T Bhuiyan, K Tanvir
    2025 28th International Conference on Computer and Information Technology … , 2025
    2025
  • Explainable Wildfire Classification with PVT and Dragonfly-Optimized Decision Trees
    SS Rafith, SM Rohan, MS Kabir, TS Sintheia, NSB Alam, K Tanvir
    2025 28th International Conference on Computer and Information Technology … , 2025
    2025
  • AI-Enhanced Leishmaniasis Classification with RegNetX with Wolf Search Algorithm
    MM Rassel, L Somoddar, MS Kabir, MS Al Huda, M Rahman, K Tanvir
    2025 28th International Conference on Computer and Information Technology … , 2025
    2025
  • BitterGNN: An Explainable Graph-Based Framework for Bitter Peptide Classification
    K Tanvir, D Gomes, M Rahman, MA Mahmud, MA Noor, MH Bhuyan
    2025 28th International Conference on Computer and Information Technology … , 2025
    2025
  • Automated Bladder Tissue Classification Using ViTXception with Explainable AI
    MS Kabir, MA Pathan, P Tamal, L Somoddar, K Tanvir, D Gomes
    2025 IEEE 7th International Conference on Sustainable Technologies For … , 2025
    2025
  • Enhanced Java Plum Leaf Disease Classification Using ShuffleNetV2 and GSA-Tuned AdaBoost
    MFK Chowdhury, MS Kabir, SS Rafith, K Tanvir, F Nazera, D Gomes
    2025 IEEE 2nd International Conference on Computing, Applications and … , 2025
    2025

MOST CITED SCHOLAR PUBLICATIONS

  • Impact of ChatGPT on Academic Performance among Bangladeshi Undergraduate Students
    K Tanvir, MS Islam, SBK Sezan, ZA Sanad, AJI Ataur
    International Journal of Research In Science & Engineering (IJRISE) 3 (05 … , 2023
    2023
    Citations: 36
  • Advancing Monkeypox diagnosis: a novel approach using a custom neural networks
    MS Kabir, MS Al Huda, K Tanvir, FT Karim, MMR Parvej, SA Tamim, ...
    2024 2nd International Conference on Information and Communication … , 2024
    2024
    Citations: 14
  • Single-Level Fusion for Enhancing Meat Quality Classification with Explainable AI
    SA Tanim, TE Shrestha, K Tanvir, MS Kabir, MF Mridha, MK Haq
    2024 IEEE International Conference on Computing, Applications and Systems … , 2024
    2024
    Citations: 13
  • Enhancing early-stage detection of melanoma using a hybrid bitdense
    K Tanvir, SA Tanim, MS Al Huda, AI Jony, MS Kabir, R Damodharan, ...
    TWIST 19 (2), 298-305 , 2024
    2024
    Citations: 11
  • Enhancing banana leaf spot disease classification using dense mobilenet v2
    MK Haq, K Tanvir, MS Kabir, NSB Alam, SK Dey, V Raju
    2024 International Conference on Advances in Computing, Communication and … , 2024
    2024
    Citations: 11
  • Clinical Insights through Xception: A Multiclass Classification of Ocular Pathologies
    K Tanvir, AI Jony, MK Haq, F Nazera, M Dass, V Raju
    Tuijin Jishu/Journal of Propulsion Technology 44 (4), 5876 - 5885 , 2023
    2023
    Citations: 11
  • Forest fire detection using ensemble deep learning model with xai
    K Tanvir, MS Kabir, ZH Anik, MR Hasan, MDT Tushar, RB Rahman
    2024 IEEE International Conference on Computing, Applications and Systems … , 2024
    2024
    Citations: 9
  • Elevating Mango Leaf Disease Classification Utilizing Dense ViT
    F Nazera, ANA Nadim, SK Dey, K Tanvir, MS Kabir
    2024 International Conference on Advances in Computing, Communication and … , 2024
    2024
    Citations: 9
  • Enhancing Corn Leaf Disease Identification with DenseViT Model
    K Tanvir, HV Lisha, R Damodharan, K Sivashanmugam
    2024 3rd International Conference on Artificial Intelligence For Internet of … , 2024
    2024
    Citations: 7
  • ResViT: An Integrated Approach Using ResNet50v2 and Vision Transformer for Enhanced Bangla Handwritten Character Recognition
    K Tanvir, MS Al Huda, MS Kabir, R Obayed, MF Attef, MA Ali
    2024 2nd International Conference on Information and Communication … , 2024
    2024
    Citations: 5
  • Enhancing Monkeypox Diagnostics: Exploring the Potential of EfficientNet and Big Transfer
    SA Tanim, K Tanvir, AR Arnob, MH Rahman, TBM Maisha, K Nur
    Journal of Image and Graphics 12 (3), 250-258 , 2024
    2024
    Citations: 5
  • Enhancing Watermelon Diseases Detection using Dense-EfficientNet and Explainable AI
    J Islam, MS Kabir, KMT Kabir, TS Sintheia, K Tanvir, D Gomes
    2024 27th International Conference on Computer and Information Technology … , 2024
    2024
    Citations: 4
  • A lightweight hybrid CNN model for classification of arsenic-induced skin lesions
    TS Sintheia, MS Kabir, K Tanvir, D Gomes, AI Jony, KT Hena
    2025
    Citations: 3
  • Potato diseases detection using Inception-BiT with Explainable AI
    MS Kabir, MNA Nadim, SA Tanim, TS Sintheia, K Tanvir, MH Bhuyan
    Proceedings of the 3rd International Conference on Computing Advancements … , 2024
    2024
    Citations: 3
  • The Safe Catch: AI Protects Your Health from Formalin-Laced Fish
    S Islam, AA Eva, NS Palock, K Tanvir, MSBK Sezan, V Raju, MK Haq, ...
    Malaysian Journal of Science and Advanced Technology 4 (3), 203-209 , 2024
    2024
    Citations: 3
  • Detecting Traffic Rule Violations and Promoting Road Safety through Artificial Intelligence
    SBK Sezan, T Rahman, K Tanvir, N Tasnim, AJI Ataur
    Journal of Artificial Intelligence, Machine Learning and Neural Network … , 2023
    2023
    Citations: 3
  • Signature Verification System: Using Big Transfer (BiT-M-R50x1) for Accurate Authentication
    K Tanvir
    Journal of Image Processing and Intelligent Remote Sensing (JIPIRS) ISSN … , 2023
    2023
    Citations: 3
  • Explainability in Orange Disease Detection through a Res-Inception Framework Integrating Deep Learning Techniques
    K Tanvir, SA Tanim, KMT Kabir, MM Rassel, MFA al Sohan
    Procedia Computer Science 258, 2597-2606 , 2025
    2025
    Citations: 2
  • An Explainable Machine Learning Framework for Obesity Classification with Optimized Support Vector Machines
    K Tanvir, MS Kabir, TS Sintheia, KT Hena, D Gomes
    Available at SSRN 5173499 , 2025
    2025
    Citations: 2
  • Mitigating Distractions caused by Social Media Overuse: A Comprehensive Approach through Personalized Digital Tools for Students
    MM Rassel, S Kabir, M Mansib, TS Sintheia, K Tanvir, MK Haq, F Nazera, ...
    Journal of Reproducible Research 2 (3), 1-12 , 2024
    2024
    Citations: 2