Incremental Hierarchical Clustering driven Automatic Annotations for Unifying IoT Streaming Data. - Edward Rolando Núñez-Valdéz; Vijender Kumar Solanki; Sivadi Balakrishna; M. Thirumaran (Int. J. Interact. Multim. Artif. Intell., 2020)

An efficient incremental clustering based improved K-Medoids for IoT multivariate data cluster analysis. - Sivadi Balakrishna; M. Thirumaran; R. Padmanaban; Vijender Kumar Solanki (Peer-to-Peer Netw. Appl., 2020)

Multi objective-based incremental clustering by fast search technique for dynamically creating and updating clusters in large data. - Sivadi Balakrishna (Clust. Comput., 2022)

Comparative Analysis of Machine Learning-Based Algorithms for Detection of Anomalies in IIoT. - Bhupal Naik D. S.; Venkatesulu Dondeti; Sivadi Balakrishna (Int. J. Inf. Retr. Res., 2022)

D-ACSM: a technique for dynamically assigning and adjusting cluster patterns for IoT data analysis. - Sivadi Balakrishna (J. Supercomput., 2022)

Unemployment Rate Future Forecasting Using Supervised Machine Learning Models. - Nareddy Vinaya; Vijender Kumar Solanki; L. Arokia Jesu Prabhu; Sivadi Balakrishna (RICE, 2023)

Progress in multi-object detection models: a comprehensive survey. - Sivadi Balakrishna; Ahmad Abubakar Mustapha (Multim. Tools Appl., 2023)

Enhancing YOLOv11 for Real-Time Object Detection: Advanced Architectures and Edge-Optimized Training Pipeline. - Sivadi Balakrishna; Shivani Yadao; Vijender Kumar Solanki (RICE, 2024)

A Two-Stage Deep Learning Approach for Optimizing Fashion Product Recommendations. - Suvarna Buradagunta; Sivadi Balakrishna (SN Comput. Sci., 2025)