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How has S. Neelima's publication output changed over time?
ScholarIQpublication output · 2011–2025
Output grew0% over the shown period — from 1 works in 2011 to 1 in 2025.
1
2
1
6
1
20112018201920242025
What are the most-cited papers on S. Neelima?
ScholarIQmost cited works
AI-driven adaptive learning for enhancing business intelligence simulation games
G. Bharathi, I. Chandra, Durga Prasada Rao Sanagana, Chaitanya Kanth Tummalachervu, Vuda Sreenivasa Rao, S. Neelima
S185496201. 202430 Citations
AI-enhanced predictive maintenance in hybrid roll-to-roll manufacturing integrating multi-sensor data and self-supervised learning
Lakshmana Phaneendra Maguluri, D. Suganthi, Girish M. Dhote, Dhiraj Kapila, Makarand Jadhav, S. Neelima
The International Journal of Advanced Manufacturing Technology. 202416 Citations
A novel ensemble approach for Twitter sentiment classification with ML and LSTM algorithms for real-time tweets analysis
T. V. Krishna, Tummalapalli Siva Rama Krishna, Srinivas Kalime, Chinta Venkata Murali Krishna, S. Neelima, Raja Rao PBV
Indonesian Journal of Electrical Engineering and Computer Science. 202413 CitationsOPEN ACCESS
SMS Spam Detection using NLP and Deep Learning Recurrent Neural Network Variants
Vangapandu Venkata Kalyani, M. V. Rama Sundari, S. Neelima, Pennada Siva Satya Prasad, Permanand Mohan, A. Lakshmanarao
20249 Citations
ANALYZING THE SUPERLATIVE SYMMETRIC CRYPTOGRAPHIC ENCRYPTION ALGORITHM ( ASCEA)
D Srinivasarao, Sushma Rani N, S. Neelima
Journal of Global Research in Computer Sciences. 20118 Citations
Related on ScholarIQ
Aditya Birla (India)
Institution
AI-driven adaptive learning for enhancing business intelligence simulation games
Paper
AI-enhanced predictive maintenance in hybrid roll-to-roll manufacturing integrating multi-sensor data and self-supervised learning
Paper
A novel ensemble approach for Twitter sentiment classification with ML and LSTM algorithms for real-time tweets analysis
Paper
SMS Spam Detection using NLP and Deep Learning Recurrent Neural Network Variants
Paper
ANALYZING THE SUPERLATIVE SYMMETRIC CRYPTOGRAPHIC ENCRYPTION ALGORITHM ( ASCEA)
Paper