[HTML][HTML] Assessing Short-range Shore-to-Shore (S2S) and Shore-to-Vessel (S2V) WiFi Communications

PM d'Orey, MG Gaitán, PM Santos, M Ribeiro… - Computer Networks, 2024 - Elsevier
Wireless communications increasingly enable ubiquitous connectivity for a large number of
nodes, applications and scenarios. One of the less explored scenarios is aquatic …

SDN-Based Multipath Data Offloading Scheme using Link Quality Prediction for LTE and WiFi Networks

S Kamath, JA Raman, P Kumar, S Singh… - IEEE Access, 2024 - ieeexplore.ieee.org
The continuous growth of mobile traffic and limited spectrum resources limits the capacity
and data rate. Heterogeneous Networks (HetNet) is a solution with multiple radio interfaces …

A Comparison of Explainable AI Models on Numeric and Graph-Structured Data

A Avinash, A Harikumar, A Nair, SK Pai… - Procedia Computer …, 2024 - Elsevier
An exponential growth of interest in the healthcare IoT over the past few years has increased
the adoption of AI. However, healthcare analytics demands highly accurate and reliable …

A Reinforcement Learning Approach for Routing in Marine Communication Network of Fishing Vessels

S Surendran, A Montresor, M Vinodini Ramesh - SN Computer Science, 2025 - Springer
The lack of affordable communication facilities to the shore remains a fundamental problem
for fishermen engaged in deep-sea fishing. The Offshore Communication Network (OCN) is …

Explainable AI in Deep Learning Based Classification of Fetal Ultrasound Image Planes

A Harikumar, S Surendran, S Gargi - Procedia Computer Science, 2024 - Elsevier
Fetal ultrasound images are widely used for visualizing fetal development during pregnancy.
These ultrasound image planes provide information about the anatomy of the fetus, thus …

An Incremental Naive Bayes Learner for Real-time Health Prediction

D Appasani, CS Bokkisam, S Surendran - Procedia Computer Science, 2024 - Elsevier
Healthcare monitoring systems have improved with the Internet of Things and machine
learning prediction models. Traditional batch machine-learning approaches cannot …

Automated Classification and Size Estimation of Fetal Ventriculomegaly from MRI Images: A Comparative Study of Deep Learning Segmentation Approaches

K Gopikrishna, NR Niranjan, S Maurya… - Procedia Computer …, 2024 - Elsevier
Fetal ventriculomegaly is one of the major risks in prenatal diagnosis, which is an
enlargement of the ventricles of the developing fetus's brain. Timely prediction of these brain …

Deep Learning Based Fetal Brain Ventricle Segmentation and Size Estimation

MP Santhosh, S Surendran - 2024 15th International …, 2024 - ieeexplore.ieee.org
Medical diagnostics with the segmentation and analysis of fetal brain ventricles assumes
paramount importance in the prediction and management of neurological disorders. This …

Fetal Heart Ultrasound Image Enhancement and Anatomical Feature Recognition via GAN and GradCAM

S Saju, S Harikumar, S Surendran… - 2024 15th International …, 2024 - ieeexplore.ieee.org
Ultrasound, an essential component of effective prenatal care, is a primary source of
valuable information concerning fetal health and development. This study presents a novel …

Ocean Wave Height Forecasting using Deep Learning Neural Networks and Optimization Techniques

ML Chowdary, P Premsai, M Dasharna… - 2023 Innovations in …, 2023 - ieeexplore.ieee.org
Ocean wave prediction is crucial for many marine applications, including navigation and
coastal engineering. Accurate wave height prediction can help reduce the risks. In this …