6 papers
A Lightweight and Explainable DenseNet-121 Framework for Grape Leaf Disease Classification
Md. Ehsanul Haque, Md. Saymon Hosen Polash, Rakib Hasan Ovi +3
Grapes are among the most economically and culturally significant fruits on a global scale, and table grapes and wine are produced in significant quantities in Europe and Asia. The…
StackLiverNet: A Novel Stacked Ensemble Model for Accurate and Interpretable Liver Disease Detection
Md. Ehsanul Haque, S. M. Jahidul Islam, Shakil Mia +4
Liver diseases are a serious health concern in the world, which requires precise and timely diagnosis to enhance the survival chances of patients. The current literature implemente…
A Modified VGG19-Based Framework for Accurate and Interpretable Real-Time Bone Fracture Detection
Md. Ehsanul Haque, Abrar Fahim, Shamik Dey +4
Early and accurate detection of the bone fracture is paramount to initiating treatment as early as possible and avoiding any delay in patient treatment and outcomes. Interpretation…
Enhancing IoT Cyber Attack Detection in the Presence of Highly Imbalanced Data
Md. Ehsanul Haque, Md. Saymon Hosen Polash, Md Al-Imran Sanjida Simla +2
Due to the rapid growth in the number of Internet of Things (IoT) networks, the cyber risk has increased exponentially, and therefore, we have to develop effective IDS that can wor…
Optimizing DDoS Detection in SDNs Through Machine Learning Models
Md. Ehsanul Haque, Amran Hossain, Md. Shafiqul Alam +3
The emergence of Software-Defined Networking (SDN) has changed the network structure by separating the control plane from the data plane. However, this innovation has also increase…
Improving Chronic Kidney Disease Detection Efficiency: Fine Tuned CatBoost and Nature-Inspired Algorithms with Explainable AI
Md. Ehsanul Haque, S. M. Jahidul Islam, Jeba Maliha +3
Chronic Kidney Disease (CKD) is a major global health issue which is affecting million people around the world and with increasing rate of mortality. Mitigation of progression of C…