173 citations · 184 across the 7 of their papers we have counts for
7 papers
An Integrated Deep Learning Model for Skin Cancer Detection Using Hybrid Feature Fusion Technique
Maksuda Akter, Rabea Khatun, Md. Alamin Talukder +2
Skin cancer is a serious and potentially fatal disease caused by DNA damage. Early detection significantly increases survival rates, making accurate diagnosis crucial. In this grou…
A Hybrid Feature Fusion Deep Learning Framework for Leukemia Cancer Detection in Microscopic Blood Sample Using Gated Recurrent Unit and Uncertainty Quantification
Maksuda Akter, Rabea Khatun, Md Manowarul Islam
Acute lymphoblastic leukemia (ALL) is the most malignant form of leukemia and the most common cancer in adults and children. Traditionally, leukemia is diagnosed by analyzing blood…
Exploring Gene Regulatory Interaction Networks and predicting therapeutic molecules for Hypopharyngeal Cancer and EGFR-mutated lung adenocarcinoma
Abanti Bhattacharjya, Md Manowarul Islam, Md Ashraf Uddin +7
With the advent of Information technology, the Bioinformatics research field is becoming increasingly attractive to researchers and academicians. The recent development of various…
MLSTL-WSN: Machine Learning-based Intrusion Detection using SMOTETomek in WSNs
Md. Alamin Talukder, Selina Sharmin, Md Ashraf Uddin +2
Wireless Sensor Networks (WSNs) play a pivotal role as infrastructures, encompassing both stationary and mobile sensors. These sensors self-organize and establish multi-hop connect…
Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction
Md. Alamin Talukder, Md. Manowarul Islam, Md Ashraf Uddin +4
Cybersecurity has emerged as a critical global concern. Intrusion Detection Systems (IDS) play a critical role in protecting interconnected networks by detecting malicious actors a…
An Optimized Ensemble Deep Learning Model For Brain Tumor Classification
Md. Alamin Talukder, Md. Manowarul Islam, Md Ashraf Uddin
Brain tumors present a grave risk to human life, demanding precise and timely diagnosis for effective treatment. Inaccurate identification of brain tumors can significantly diminis…
A Dependable Hybrid Machine Learning Model for Network Intrusion Detection
Md. Alamin Talukder, Khondokar Fida Hasan, Md. Manowarul Islam +5
Network intrusion detection systems (NIDSs) play an important role in computer network security. There are several detection mechanisms where anomaly-based automated detection outp…