Md. Samin Morshed Data-verified
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Biography and Research Information
OverviewAI-generated summary
Md. Samin Morshed's research focuses on the application of machine learning and artificial intelligence techniques across various domains. His work includes the development of deep learning models for fruit quality assessment and date fruit classification, as well as age estimation from facial images using transfer learning. Morshed has also investigated the use of gradient-weighted class activation mapping for mycological examinations of microscopic fungi images and predicting mushroom edibility through effective classification and feature selection methods. His recent publications also explore the integration of IoT and blockchain for remote pregnancy care coordination and entity resolution using transformer models for synthetic datasets.
His research network includes collaborations with Mariofanna Milanova and Md Rizwanul Kabir at the University of Arkansas at Little Rock, with whom he has co-authored multiple publications. Morshed's scholarship metrics include an h-index of 3, with 10 total publications and 56 citations.
Metrics
- h-index: 4
- Publications: 10
- Citations: 62
Selected Publications
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Entity Resolution Using Transformers for Synthetic Datasets (2025)
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Semantic Entity Resolution on Synthetic Datasets: A Transformer-Centric Approach (2025)
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Mycological Examination of Microscopic Fungi Images with Deep Learning and Gradient Weighted Class Activation Mapping Visualization (2024)
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Intrapartum fever prediction for pregnant woman from microbial data (2024)
Collaboration Network
Top Collaborators
- Fruit Quality Assessment with Densely Connected Convolutional Neural Network
- Date Fruit Classification with Machine Learning and Explainable Artificial Intelligence
- Mycological Examination of Microscopic Fungi Images with Deep Learning and Gradient Weighted Class Activation Mapping Visualization
- Predicting Mushroom Edibility with Effective Classification and Efficient Feature Selection Techniques
- IoT-Blockchain in Remote Pregnancy Care Coordination
Showing 5 of 6 shared publications
- Fruit Quality Assessment with Densely Connected Convolutional Neural Network
- Age Estimation from Facial Images using Transfer Learning and K-fold Cross-Validation
- Fruit Quality Assessment with Densely Connected Convolutional Neural Network
- Age Estimation from Facial Images using Transfer Learning and K-fold Cross-Validation
- IoT-Blockchain in Remote Pregnancy Care Coordination
- Predicting Mushroom Edibility with Effective Classification and Efficient Feature Selection Techniques
- Intrapartum fever prediction for pregnant woman from microbial data
- Date Fruit Classification with Machine Learning and Explainable Artificial Intelligence
- IoT-Blockchain in Remote Pregnancy Care Coordination
- Semantic Entity Resolution on Synthetic Datasets: A Transformer-Centric Approach
- Entity Resolution Using Transformers for Synthetic Datasets
- Semantic Entity Resolution on Synthetic Datasets: A Transformer-Centric Approach
- Entity Resolution Using Transformers for Synthetic Datasets
- Semantic Entity Resolution on Synthetic Datasets: A Transformer-Centric Approach
- Entity Resolution Using Transformers for Synthetic Datasets
- Age Estimation from Facial Images using Transfer Learning and K-fold Cross-Validation
- Fruit Quality Assessment with Densely Connected Convolutional Neural Network
- Fruit Quality Assessment with Densely Connected Convolutional Neural Network
- Predicting Mushroom Edibility with Effective Classification and Efficient Feature Selection Techniques
- Date Fruit Classification with Machine Learning and Explainable Artificial Intelligence
- Date Fruit Classification with Machine Learning and Explainable Artificial Intelligence
- Fruit Quality Assessment with Densely Connected Convolutional Neural Network
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