Md. Samin Morshed
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
Researcher
Also affiliated: University of Information Technology and Sciences (2023); Asian University of Bangladesh (2023); Islamic University of Technology (2021–2023)
Faculty Researcher
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Md. Samin Morshed's research focuses on the application of machine learning and artificial intelligence techniques to diverse domains. His work includes developing models for fruit quality assessment using densely connected convolutional neural networks and classifying date fruits with machine learning and explainable AI. Morshed has also investigated age estimation from facial images through transfer learning and explored deep learning for mycological examination of microscopic fungi. His recent publications also address entity resolution using transformers for synthetic datasets and the integration of IoT and blockchain in remote pregnancy care coordination. Morshed has a h-index of 4 with 65 citations across 10 publications. He has collaborated with Mariofanna Milanova, Md Rizwanul Kabir, and John R. Talburt, with whom he shares multiple publications.
Metrics
- h-index: 4
- Publications: 10
- Citations: 68
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
- 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
- Intrapartum fever prediction for pregnant woman from microbial data
- Intrapartum fever prediction for pregnant woman from microbial data
- Intrapartum fever prediction for pregnant woman from microbial data
- Intrapartum fever prediction for pregnant woman from microbial data
- Intrapartum fever prediction for pregnant woman from microbial data
- Mycological Examination of Microscopic Fungi Images with Deep Learning and Gradient Weighted Class Activation Mapping Visualization
- Mycological Examination of Microscopic Fungi Images with Deep Learning and Gradient Weighted Class Activation Mapping Visualization
- Mycological Examination of Microscopic Fungi Images with Deep Learning and Gradient Weighted Class Activation Mapping Visualization
- Mycological Examination of Microscopic Fungi Images with Deep Learning and Gradient Weighted Class Activation Mapping Visualization
- Mycological Examination of Microscopic Fungi Images with Deep Learning and Gradient Weighted Class Activation Mapping Visualization
- Semantic Entity Resolution on Synthetic Datasets: A Transformer-Centric Approach
- Entity Resolution Using Transformers for Synthetic Datasets
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