Supporting QoS Differentiation in Energy-Constrained Cognitive Radio Networks. - Lakshmana Rao Kalabarige; Shanti Chilukuri (Wirel. Pers. Commun., 2017)

On the convergence and optimality of the firefly algorithm for opportunistic spectrum access. - Lakshmana Rao Kalabarige; Sireesha Rodda; Shanti Chilukuri (Int. J. Adv. Intell. Paradigms, 2021)

Multilayer Stacked Ensemble Learning Model to Detect Phishing Websites. - Lakshmana Rao Kalabarige; Routhu Srinivasa Rao; Ajith Abraham; Lubna Abdel Kareim Gabralla (IEEE Access, 2022)

Symptom based COVID-19 test recommendation system using machine learning technique. - Lakshmana Rao Kalabarige; Hima Bindu Maringanti (Intell. Decis. Technol., 2022)

A Boosting-Based Hybrid Feature Selection and Multi-Layer Stacked Ensemble Learning Model to Detect Phishing Websites. - Lakshmana Rao Kalabarige; Routhu Srinivasa Rao; Alwyn R. Pais; Lubna Abdel Kareim Gabralla (IEEE Access, 2023)

Boosting Pineapple Maturity Classification: Impact of Data Augmentation and Visual Transformer Integration With Transfer Learning. - Lakshmana Rao Kalabarige; A. Venkata Ramana; Routhu Srinivasa Rao; M. Raviraja Holla (IEEE Access, 2024)

Multimodal Imputation-Based Multimodal Autoencoder Framework for AQI Classification and Prediction of Indian Cities. - Routhu Srinivasa Rao; Lakshmana Rao Kalabarige; M. Raviraja Holla; Aditya Kumar Sahu (IEEE Access, 2024)

Multimodal imputation-based stacked ensemble for prediction and classification of air quality index in Indian cities. - Routhu Srinivasa Rao; Lakshmana Rao Kalabarige; Bhavya Alankar; Aditya Kumar Sahu (Comput. Electr. Eng., 2024)