Md. Milon Islam

Radiology, Nuclear Medicine and Imaging · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Radiology, Nuclear Medicine and Imaging — 23 citations into it
• Artificial Intelligence — 20 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it

Whom Md. Milon Islam trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Mohammad Rahimzadeh
2. Joseph Paul Cohen
3. Ezz El-Din Hemdan
4. Charu C. Aggarwal

Papers from Md. Milon Islam's perspective

Ordered by how strongly the researchers Md. Milon Islam trusts endorse each paper. Same corpus, a different order for every researcher.

1. COVID-19 Image Data Collection
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. A Tutorial on Support Vector Machines for Pattern Recognition
4. Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks (Physical and Engineering Sciences in Medicine)
5. A Framework for Clustering Evolving Data Streams
6. Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR (Radiology)
7. Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases
8. ImageNet classification with deep convolutional neural networks
9. Coronavirus Disease 2019 (COVID-19): Role of Chest CT in Diagnosis and Management. (AJR. American journal of roentgenology)
10. COVIDX-Net: A Framework of Deep Learning Classifiers to Diagnose COVID-19 in X-Ray Images (arXiv.org)

Their papers

• Development of Smart Healthcare Monitoring System in IoT Environment (2020) — 457 citations
• A combined deep CNN-LSTM network for the detection of novel coronavirus (COVID-19) using X-ray images (2020) — 617 citations
• Attack and anomaly detection in IoT sensors in IoT sites using machine learning approaches (2019) — 715 citations