Jyotir Moy Chatterjee

Microprocessors and microsystems · 2020–2021

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

Papers from Jyotir Moy Chatterjee's perspective

Ordered by how strongly the researchers Jyotir Moy Chatterjee trusts endorse each paper. Same corpus, a different order for every researcher.

1. Random Forests
2. An Automatic Learning-Based Framework for Robust Nucleus Segmentation (IEEE Transactions on Medical Imaging)
3. COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest Radiography Images (arXiv.org)
4. A Hybrid Feature Extraction Method With Regularized Extreme Learning Machine for Brain Tumor Classification (IEEE Access)
5. A Short Introduction to Boosting
6. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China (The Lancet)
7. A hybrid method for MRI brain image classification (Expert systems with applications)
8. Middle East Respiratory Syndrome (The Lancet)
9. Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts (IEEE Access)
10. Brain Tumor Classification Using Convolutional Neural Networks (Biomedical & Pharmacology Journal)

Their papers

• Performance of deep learning vs machine learning in plant leaf disease detection (2021) — 546 citations
• A Hybrid CNN-SVM Threshold Segmentation Approach for Tumor Detection and Classification of MRI Brain Images (2021) — 432 citations
• COVID-19 Patient Health Prediction Using Boosted Random Forest Algorithm (2020) — 426 citations