Hybrid gradient descent spider monkey optimization (HGDSMO) algorithm for efficient resource scheduling for big data processing in heterogenous environment. - V. Seethalakshmi; Govindasamy Vaiyapuri; Akila Venkatesan (J. Big Data, 2020)

Secure access of resources in software-defined networks using dynamic access control list. - J. Ramprasath; V. Seethalakshmi (Int. J. Commun. Syst., 2021)

Improved Network Monitoring Using Software-Defined Networking for DDoS Detection and Mitigation Evaluation. - J. Ramprasath; V. Seethalakshmi (Wirel. Pers. Commun., 2021)

Mitigation of Malicious Flooding in Software Defined Networks Using Dynamic Access Control List. - J. Ramprasath; V. Seethalakshmi (Wirel. Pers. Commun., 2021)

A review on deep learning in medical image analysis. - S. Suganyadevi; V. Seethalakshmi; K. Balasamy 001 (Int. J. Multim. Inf. Retr., 2022)

Real-coded multi-objective genetic algorithm with effective queuing model for efficient job scheduling in heterogeneous Hadoop environment. - V. Seethalakshmi; Govindasamy Vaiyapuri; Akila Venkatesan (J. King Saud Univ. Comput. Inf. Sci., 2022)

CVD-HNet: Classifying Pneumonia and COVID-19 in Chest X-ray Images Using Deep Network. - S. Suganyadevi; V. Seethalakshmi (Wirel. Pers. Commun., 2022)

Deep recurrent learning based qualified sequence segment analytical model (QS2AM) for infectious disease detection using CT images. - S. Suganyadevi; V. Seethalakshmi (Evol. Syst., 2024)

Deep Learning Based Alzheimer Disease Diagnosis: A Comprehensive Review. - S. Suganyadevi; A. Shiny Pershiya; K. Balasamy 001; V. Seethalakshmi; Saroj Bala; Kumud Arora (SN Comput. Sci., 2024)

Medical Image Analysis Through Deep Learning Techniques: A Comprehensive Survey. - K. Balasamy 001; V. Seethalakshmi; S. Suganyadevi (Wirel. Pers. Commun., 2024)

FACNN: fuzzy-based adaptive convolution neural network for classifying COVID-19 in noisy CXR images. - S. Suganyadevi; V. Seethalakshmi (Medical Biol. Eng. Comput., 2024)

HCO-RLF: Hybrid classification optimization using recurrent learning and fuzzy for COVID-19 detection on CT images. - K. Balasamy 001; V. Seethalakshmi (Biomed. Signal Process. Control., 2025)