Publications

Journal Publications (Highest Impact Factor: 28.0, # IEEE Transactions: 04 )

Selected Publications:

1. Annushree B, Damodar E, Diwakar T., Cheruku Ramalingaswamy, "Survey on Brain-Computer Interface: An Emerging Computational Intelligence Paradigm", ACM Computing Surveys, (I.F. 28.00, SCI)   [Q1]

2. Deepthi K, Ilaiah K, Ramalignaswamy Cheruku, Gradient-Reversed Domain-Adaptive Multi-Modal Cross-Attention Network for Robust Face Anti-Spoofing, IEEE Transactions on Biometrics, Behavior, and Identity Science, 2025 [Q1] 

3. Ramesh Donapti,  Ramalingaswamy Cheruku, Prakask Kodali, Real-time Seed Detection and Germination Analysis in Precision Agriculture: A Fusion Model with U-Net and CNN on Jetson Nano, IEEE Transactions on AgriFood Electronics, 1(2), 145-155, 2023 [Q1]

4. Hemraj, Mridula Verma, Ramalingaswamy Cherku, DSFNet: Video Salient Object Detection using A Novel Lightweight Deformable Separable Fusion Network, IEEE Transactions on Instrumentation and Measurement, 2024 (IF 5.6, SCI) [Q1]

5. Hemraj Singh, Mridula Verma, Ramalingaswamy Cheruku, "Novel Dilated Separable Convolution Networks for Efficient Video Salient Object Detectioninthe Wild", IEEE Transactions on Instrumentation and Measurement, 72, 2023 (IF 5.6, SCI) [Q1]

6. Damodar Reddy E, Amrutha L, Cheruku Ramalingaswamy, Venkatanareshbabu K, "An Efficient Load Balancing of Gateways using Improved Shuffled Frog Leaping Algorithm and Novel Fitness Function for WSNs", IEEE Sensors Journal, 17(20), 6724 - 6733, 2017. [IF: 4.3, SCI].  [Q1]

7. Cheruku Ramalingaswamy, Damodar Reddy Edla, Venkatanareshbabu K, D Ramesh,"RST-BatMiner: A Fuzzy Rule Miner Integrating Rough Set Feature Selection and Bat Optimization for Detection of Diabetes Disease", Applied Soft Computing, 2018 [Elsevier, IF: 8.7, SCI]  [Q1]

8. Cheruku Ramalingaswamy, Damodar Reddy Edla, and Venkatanareshbabu Kuppili. "SM-RuleMiner: Spider monkey based rule miner using novel fitness function for diabetes classification." Computers in Biology and Medicine, 81, 79-92, 2017. [Elsevier, IF: 7.7, SCI]  [Q1]

9. Ramalingaswamy Cheruk et al. Enhancing Disease Diagnosis Performance using a Novel Genetic Algorithm and K-means Clustering-Based Ensemble Model,  Biomedical Signal Processing and Control  [Elsevier, SCI, IF: 5.1] 2024  [Q1]

10. Ramalingaswamy Cheruku et al. Design of a fingerprint template protection scheme using elliptical structures. ICT Express 7(4): 497-500 (2021) (Elsevier, IF: 5.4) [Q1]

11. Hemraj, Mrudula, Ramalingaswamy Cherku, DMFNet: Geometric Multi-Scale Pixel-level Contrastive Learning for Video Salient Object Detect, International Journal of Multimedia  Information (Accepted), 2025, [Springer, IF: 3.6] [Q1]

12. Ragini, Prakash, Ramalingaswamy Cheruku, DAMNet:  Light-weight Dual Attention Mixed Network for Efficient Image Deraining, Neural Computing and Applications (Springer, IF: 4.5, 2024) [Q1]

13. Ramalingaswamy Cheruku et al. Spatial Spiking Neural Network for Classification of EEG Signals for Concealed Information Test, Multimedia Tools and Applications. [Springer, IF:3.6], 2024

14. Deepthi, Ilaiah K, Ramalignaswamy Cheruku, CCLHF-Net: Constrained Convolution Layer and Hybrid Features based SkipConnection Network for Image Forgery Detection, Arabian Journal of Science and Engineering, [Springer, SCI, IF: 2.9], 2024 [Q1]

15. Ramesh,  Ramalingaswamy Cheruku, Prakask Kodali, "SeedAI: A Novel Seed Germination Prediction System using Dual Stage Deep Learning Framework", Environmental Research Communications, [IF:2.9], 2023 [Q1]

16. Damodar Reddy Edla, Diwakar Tripathi, Cheruku Ramalingaswamy, Venkatanareshbabu Kuppili, " An Efficient Ensemble Framework with BPSOGA-based Feature Selection: A Case study on Credit Scoring Datasets ", Arabian Journal of Science and Engineering. [Springer, IF: 2.9, SCI Indexed] [Q1]

17. Cheruku Ramalingaswamy et al. "Sentiment Classification with Modified RoBERTa and Recurrent Neural Networks," Multimedia Tools and Applications, 2023, (Springer, IF: 3.6, SCI) [Q1]

18. Hemraj Singh, Mridula Verma, Ramalignaswamy Cheruku, DAMFNet: Breaking Computational Barriers in Video Salient Object Detection with Multi-Scale Deformable Appearance-Motion Fusion, Arabian Journal of Science and Engineering, [Springer, SCI, IF: 2.9], 2025 [Q1]

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19. Ragini, Prakash, Ramalingaswamy Cheruku, S2VSNet: Single Stage V-Shaped Network for Image Deraining & Dehazing, Digital Signal Processing (Elsevier, IF 2.5, 2024)

20. Ragini T, Prakash K, Cheruku Ramalingaswamy ,"DeTformer: A Novel Efficient Transformer Framework for Image Deraining", Circuits, Systems & Signal Processing, 2023 [Springer, SCI, IF:2.3]

21. Ramalingaswamy Cheruku, et al.  BT-CNN: A Balanced Binary Tree Architecture for Classification of Brain Tumour using MRI Imaging, Frontiers in Physiology  [Frontieres, IF: 4.0], 2024

22. Ragini, Prakash, Ramalingaswamy Cheruku, Joint Rain Streaks & Haze Removal Network for Object Detection, CMC-Computers, Materials & Continua, 79(3), 2024 [IF: 3.1], 

23. Arukonda Srinivas, Cheruku Ramalingaswamy, "Nested Genetic Algorithm based Classifier Selection and Placement in Multi-Level Ensemble Framework for Effective Disease Diagnosis", Computer Methods in Biomechanics and Biomedical Engineering, [T& F, SCI, IF: 1.6], 2023

24. Ramalingaswamy Cheruk et al. Detection of COVID-19 using Edge Devices by a Light-Weight Convolutional Neural Network from Chest X-Ray Images, BMC Medical Imaging, [Springer, IF: 2.7], 2023

25. Arukonda Srinivas and Cheruku Ramalingaswamy, "A Novel Stacking Framework with PSO Optimized SVM for Effective Disease Classification", JIFS, [IOS, IF: 2, SCI]

26. Cheruku Ramalingaswamy, Damodar Reddy Edla, and Venkatanareshbabu Kuppili. "Diabetes Classification using Radial Basis Function Network by Combining Cluster Validity Index and BAT Optimization with Novel Fitness Function." International Journal of Computational Intelligence Systems, 10(1), 247-265, 2017. [Springer IF: 2.9, SCI Indexed].

27. Cheruku Ramalingaswamy et al. "Automatic Disease Diagnosis using Optimized Weightless Neural Networks for Low-Power Wearable Devices." Healthcare Technology Letters, 4(4), 122-128, (2017) [IET, ESCI, IF:2.1]

28. Cheruku Ramalingaswamy, Damodar Reddy Edla, and Venkatanareshbabu Kuppili. "An Optimized and Efficient Radial Basis Neural Network using Cluster Validity Index for Diabetes Classification", The International Arab Journal of Information Technology, [IF: 0.9, SCI].

29. Damodar Reddy E, Mahesh Chowdary K, Cheruku Ramalingaswamy "SCE-PSO Based Clustering Approach for Gateways Load Balancing in Wireless Sensor Networks", Wireless Networks, [Springer, SCI, I.F. 3]

30. Damodar  E, Amrutha L, Cheruku Ramalingaswamy, "Shuffled Complex Evolution Approach for Load Balancing of Gateways in WSNs", Wireless Personal Communications, 2017. [Springer, IF: 2.00, SCI Indexed)

31. Damodar E, Mahesh K, Cheruku Ramalingaswamy, "A PSO-based Routing using Novel Fitness Function for Improving Gateways Lifetime in WSNs", Wireless Personal Communications [Springer, SCI, I.F. 2.00]

32. Ashan Hussain, Keshavamurthy, Cheruku Ramalingaswamy, "Dynamic Multi-Layer Ensemble Classification Framework for Social Venues using Binary Particle Swarm Optimization", Wireless Personal  Communications, [Springer, SCI Indexed, I.F. 2.00]

33. Diwakar Tripathi, Damodar Reddy Edla, Cheruku Ramalingaswamy, Venkatanareshbabu Kuppili "A Novel Hybrid Credit Scoring Model based on Ensemble Feature Selection and Multi-layer Ensemble Classification" Journal of Computational Inteligence [Willey, SCI Indexed, I.F. 2.8]

34. B. Naresh Kumar Reddy, Cheruku Ramalingaswamy, R. Nagulapalli, and Dharavath Ramesh, "A Novel 8T SRAM with Improved Cell Density" Journal of Analog Integrated Circuits and Signal Processing [Springer, SCI, I.F. 1.3]

35. Hemraj, Mrudula, Ramalingaswamy Cherku, HSNet: A Novel Edge-preserving Hierarchical Separable Network for Video Shadow Detection ", Circuits Systems and Signal Processing [Springer, SCI, IF: 2.3]

36. Shubam Dhodla, Damodar Reddy Edla, Anushree Bublani, Cheruku Ramalingaswamy, VNB "Lie Detection using Extreme Learning Machine: A Concealed Information Test based on Short-Time Fourier Transform and Binary Bat Optimization using a Novel Fitness Function" Journal of Computational Intelligence [Willey, SCI, I.F. 2.8]

37. Diwakar Tripathi, Damodar Reddy Edla, Cheruku Ramalingaswamy, "Hybrid Credit Scoring Model Using Neighborhood Rough Set and Multi-layer Ensemble Classification" Journal of Intelligent and Fuzzy Systems, 2017, [IOS Press, SCI Indexed, I.F. 2]

38. Ramalingaswamy Cheruku and Damodar Reddy Edla, "Selector: PSO as Model Selector for Dual Stage Diabetes Network" in Journal of Intelligent Systems. [De-Gruter, I.F: 3.0]

39. Cheruku Ramalingaswamy et al., Trust-Based Permissioned Blockchain Network for Identification and Authentication of Internet of Smart Devices: An E-Commerce Prospective, Journal of Interconnection Networks [IF: 0.9]

40. Cheruku Ramalingaswamy et al., "Complex Human Activity Recognition with Deep Inception Learning and Squeeze-Excitation Framework", Journal of Information Assurance and Security 17(2), 2022,  (ESCI)

41. Cheruku Ramalingaswamy et al.,"Permissioned Blockchain-based Collaborative Intrusion Detection System to Secure Internet of Things Against DDoS Attacks", Journal of Information Assurance and Security 16(5), 2021,  (ESCI)

42. Cheruku Ramalingaswamy et al. "A Novel Approach to Predict High Blood Pressure using ABF Function" International Journal of Modern Education and Computer Science [Scopus]

43. Cheruku Ramalingaswamy et al. "High Blood Pressure Prediction based on AAA++ using Machine Learning " Journal of Cogent Engineering [T&F, ESCI and Scopus]

44. Damodar Reddy Edla and Cheruku Ramalingaswamy, "Diabetes-Finder: A Bat Optimized Classification System for Type-2 Diabetes" Procedia Computer Science, 115, 235–242, 2017, [Elsevier, Scopus]

45. Ramesh, Prakash, Ramalingaswamy Cheruku, AI-Enhanced Seed Quality Assessment and Environmental Control Using MASK RCNN, IJMECS  (Under Review)

46. Ramalingaswamy Cheruku et al. Accurate Output Power Prediction in TENG devices using Artificial Intelligence: A Comparative Analysis, IAJIT  (Under Review)

47. Ramalingaswamy Cheruk et al. MMO-EvoBagging: Genetic Algorithm and Multi-Modal Optimization based Bagging for Effective Disease Diagnosis, IEEE Transactions on Artificial Intelligence (Under Review)

48. Ramesh, Ramalingaswamy Cheruku, Prakash, AI-Enhanced Seed Quality Assessment through Environmental Control Using Mask R-CNN, Agronomy [IF:3.7], 2024

1. Hemraj Singh, Mridula Verma and Ramalingaswamy Cheruku,  Efficient Lightweight Model for Video Salient Object Detection for IoT and WoT Applications, WWW 2023 (CORE A* Conference) (USA)

2. Hemraj Singh, Mridula Verma and Ramalingaswamy Cheruku, "VS-NET: MULTI-SCALE SPATIOTEMPORAL FEATURES FOR LIGHTWEIGHT VIDEO SALIENT  DOCUMENT DETECTION" in The 34th IEEE Conference on Tools with Artificial Intelligence 2022 (CORE A Conference) (USA)

3. Cheruku Ramalingaswamy et al. "PSO-RBFNN: A PSO-based Clustering Approach for RBFNN Design to Classify Disease Data", in 26 th International Conference on Artificial Neural Networks (ICANN), Italy, LNCS 10614, pp. 411-419, 2017. (CORE B)

4. Ramalingaswamy Cheruku et al."Effective Diabetes Prognosis using Deep Learning Pipeline ", TENCON 2023, Thailand 

5. Ramalingaswamy Cheruku et al. "Parametric Optimization of Magnetic Abrasive Finishing Process Using Genetic Algorithm and Particle Swarm Optimization", TENCON 2023, Thailand 

6. Ramalingaswamy Cheruku et al. "Improvement in QCN with BIER for Chassis Topology ", TENCON 2023, Thailand 

7. Ramalingaswamy Cheruku et al. "Cancelable Iris Template Generation using Weber Local Descriptor", TENCON 2023, Thailand 

8. Ramalingaswamy Cheruku et al. "Predicting Wildfire using Live Fuel Moisture Content with Machine Learning" in 19th INDICON 2022, Kerala.

9. Ilaiha Kavati, Sureshbabu, Ramalingaswamy Cheruku  "Real-Time Traffic Sign Recognition and Classification using Deep Learning" in 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020)

10. Cheruku Ramalingaswamy et al. "A Bi-Level Cascaded Ensemble Framework for Effective Disease Diagnosis”, in 31 st TENCON, 2019, India.

11. Cheruku Ramalingaswamy et al. "Intelli-DRM: An Intelligent Computational Model for Forecasting Severity of Dia-betes Mellitus" in 8 th International Conference on Computing Communication and Networking Technologies (ICCCNT), IEEE, IIT Delhi, 2017

12. Cheruku Ramalingaswamy et al. "Bin-BB: Binning with Branch & Bound feature selection for improved diabetes classication" in 14 th INDICON, IEEE, IIT Roorkee, India, 2017

13. Ramalingaswamy Cheruku, Diwakar Tripathi, Narasimha Reddy Y and Sathya Prakash Racharla "Review on RBFNN Design Approaches: A Case Study on Diabetes Data" in LAMDA, Springer, NIT Goa, India, 2017

14. Diwakar Tripathi, Ramalingaswamy Cheruku and Annushree Bablani"Relative Performance Analysis of Ensemble Frameworks and Dimenstionality Reduction Approaches for Credit Scoring Datasets" in 1 st International Conference Latest Advances in Machine learning and DAta Science, Springer, NIT Goa, India, 2017

15. Damodar Reddy Edla, Diwakar Tripathi, Venkata Naresh Babu and Ramalingaswamy Cheruku "Survey on Clustering Techniques" in ICICCT-2018, IEEE, India, 2018

16. Amrutha Lipare, Damodar Reddy Edla, Ramalingaswamy Cheruku, Diwakar Tripathi "GWO-GA based Load Balanced and Energy Efficient Clustering Approach for WSN"
    in SmartCom-2019, IEEE, Bangkok, 2019

17. Naresh Kumar reddy, Srangam,Veeraiha, Ramalingaswamy Cheruku, “SRAM cell with better read and write stability with minimum area”, 31 st TENCON, 2019, India.

18. Damodar Reddy Edla , Vilas Deshmukh , Ramalingaswamy Cheruku Saheeka SD and Brijesh Yadav,"A Novel Green Stable Evolutionary Routing Algorithm for Energy Efficiency in WSNs" in 7 th (ICACCI), MIT Manipal, India, 2017.

19. Satyanarayana Nimmala, Ramadevi Y., Srinivas Naik, Ramalingaswamy Cheruku "Predicting High Blood Pressure using Decision Tree Based Algorithm" in LAMDA Springer, NIT Goa, India, 2017

20. G Kiran Kumar, Ilaiah Kavati, Koppula Srinivas Rao and Ramalingaswamy Cheruku "Spatial Co-location Pattern Mining using Delaunay Triangulation" in LAMDA, Springer, NIT Goa, India, 2017

21. Srinivas Arukonda and Ramalingaswamy Cheruku, Hybrid Optimization of Bag Composition for Disease Diagnosis: Integrating Teaching-Learning-Based Optimization with Genetic Algorithm.,4th International Conference on Advanced Engineering Optimization Techniques, 2023, SVNIT Surat

22. Srinivas Arukonda and Ramalingaswamy Cheruku, Diversified Ensemble Learning: Integrating Bagging and TeachingLearning-Based Optimization with Pairwise Dissimilarity Measure, 4th International Conference on Advanced Engineering Optimization Techniques, 2023, SVNIT Surat

23. Srinivas Arukonda and Ramalingaswamy Cheruku, A Novel Stacking Framework with GWO-based Feature Selection for Effective Disease Diagnosis, INDICON 2023

24. Srinivas Arukonda and Ramalingaswamy Cheruku,  A TLBO Based Bagging Approach for Effective Disease Diagnosis, CODS-COMAD 2024, IIIT Bangalore

25. Puppala Ravi Sankar, Kodali Prakash, Cheruku Ramalingaswamy, Rajaboina Rakesh Kumar, K Uday Kumar and G Venkatesh, Triboelectric Nanogenerator Based on Different Polymers: Experimental and Simulation Study, INDICON 2023

26. Joydeep, Ramalingaswamy Cheruku et al. Enhancing Ensemble Models Through Diversity Using K-Means for Effective Diabetes Classification, CONNECT 2024, IISc Bangalore, 2024

1. Granted an Indian Patent "SALT TOLERANCE MONITORING SYSTEM " (Application Number: 202341017040)

2. Granted a Australian Patent  on "A SYSTEM AND METHOD FORDETERMINING TRUTHFUL AND DECEPTIVE STATE OF A PERSON", (Application Number: 2021102773)

3. Published an Indian Patent "A SYSTEM AND METHOD FOR DETERMINING TRUTHFUL AND DECEPTIVE STATE OF A PERSON", (Application Number: 202121022140)

1. PI, RSM Project, Design and Development of Deep Learnig Models for Diabetic Rationopathy, 2021-2023, Rs. 5,00,000/-. (Completed) 

1. Cheruku Ramalingaswamy, Damodar Reddy Edla, and Venkatanareshbabu Kuppili. "Machine Learning Approaches for Diabetes Classification: A survey", McGrawhill, 2016

2. Damodar Reddy Edla, Padunaik, Tejaswini, Hareesh, Cheruku Ramalingaswamy "Credit Scoring using Birds Swarm Optimization", Taylor & Francis and CRC Press, 2017

3. Srinivas Naik, Cheruku Ramalingaswamy, "Effects of COVID-19 Pandemic in Obese and Asthma Patients: A Systematic Review", Intelligent healthcare (Springer book), 2020

4. Cheruku Ramalingaswamy, et al. WSN Lifetime Optimization using IBA, Role of Nature-Inspired Algorithms in real-life Problems. Springer 2024

5. Srinivas Arukonda and Ramalingaswamy Cheruku, Hybrid Optimization of Bag Composition for Disease Diagnosis: Integrating Teaching-Learning-Based Optimization with Genetic Algorithm, Advancing Healthcare through Decision Intelligence, Elsevier, 2025

6. Cheruku Ramalingaswamy, et al. Feature Selection using Grey Wolf Optimization for Diagnosis of Diabetes Diseases, Role of Nature-Inspired Algorithms in real-life Problems. Springer 2024

7. Srinivas Arukonda and Ramalingaswamy Cheruku, "Dynamic Weighted Ensemble Approach with Entropy-based Diversity Measure for Disease Diagnosis using TLBO Optimization", Decision Sciences in Bioinformatics: Theory and Practice, CRC Press Taylor & Francis 

8. Janaki Devi M, Ramalingaswmy Cheruku, Rami Naidu, "Early Detection of Alzheimer's Disease through Tau-PET Image Analysis Using CNN", Algorlthms in Advanced Artificial Intelligence © 2024 Taylor & Francis Group, London, ISBN 978-1-032-86798-4 

Under my guidance, 2 Schakors Awarded a Ph.D degree, and 8  Ph.D.s are on going

1. Mr. Arukonda Srinivas [Reg. No: 721089], Jan 2021-Jan 2024: "Ensemble Learning and Optimization"  Awarded 

2. Mr.  Hemraj Singh [Reg. No: 720079], July 2020-tilldate "Video Salient Object Detection": Awarded 

3. Ms. Maddala Janakidevi, [Reg. No: 21CSREP14], Jan 2022-tilldate: "EEG Signal Analysis using Deep Learning Models": Ongoing

4. Ms. E. Uma Maheshwari [Reg. No: 23CSR2R13], Jan 2024-tilldate, Class Imbalance and Ensemble Learning:   Ongoing

5. Ms. Nikhila Rame [Reg. No. 23CSR2P01], Jan 2024-tilldate, Precision Agriculture using Deep Learning:   Ongoing

6. Ms. Mounika [Reg. No.23CSR2P15],  Jan 2024-tilldate, Machine Learning and Optimization    Ongoing 

7. Mr. Talluri Haribabu [ Reg. No. 24CSR1P02] , July 2024-tiildate, Image Processing and Optimization, Ongoing 

8. Mr. Suresh [Reg. No. 24CSR1P37], July 2024-Tilldate, Machine Learning, Ongoing

9. Ms. Spandana Vonguri [Reg. No. 24CSR2P03], Dec 2024-Tilldate, Machine Learning, Ongoing

10. Mr. Ananth Nath Talla [Reg. No. 24CSR2P01], Dec 2024-Tilldate, Machine Learning, Ongoing

1. Organized 10 days FDP on "Advanced Machine Learning Techniques: From Concepts to Real-World Implementation " from 03-02-2025 to 12-02-2025 with CBIT Hyderabad and EICT NIT Warangal

2. Organized 10 days FDP on "Harnessing the Power of AI Deep Learning and Machine Learning Techniques" from 02-01-2025 to 12-01-2025 with Jeppiaar Institute of Technology  Chennai and EICT NIT Warangal

1. Organized 10 days FDP on "Recent Trends in Machine Learning and Deep Learning" from 16-07-2024 to 26-07-2024 with Vidyavardaka College of Engineering  Mysure and EICT NIT Warangal

2. Organized 10 days FDP on "Deep Learning and Machine Learning: Theory, Practice and Applications" from 02-12-2024 to 12-12-2024 with Jeppiaar Institute of Technology  Chennai and EICT NIT Warangal

3. 
   

1. Organized 10 days FDP on"Recent Trends in VLSI and MEMS for IoT Applications" from 16-5-2022 to 25-5-2022

2. Organized 10 days FDP on"Advances in Cyber Secuirty and AI" from 6-6-2022 to 16-6-2022

3. Organized 10 days FDP on"Reserch Challenges and Hands on Practice in Data Analytics and AI" from 21-7-2022 to 31-7-2022

4. Organized 10 days FDP on"Neural Computing for Machine Learning Techniques and Its Applications in Cryptography" from 8-8-2022 to 16-8-2022

5. Organized five day  FDP on  "Machine Learning Models for Decision Making" during Aug 25-30, 2022

6. Organized two week FDP on"Machine Leaning and Soft Computing Approaches for Real-time Applications" from 24-9-2022 to 1-10-2022

1. Organized 10 days FDP on" Reseach Challenges, Issues and Trends in Soft Computing and Machine Learning" from 9-8-2021 rto 18-8-2021

2. Organized 10 days FDP on"Emerging Technologies: AI, Bigdata and Block chain" from 16-9-2021 rto 25-9-2021

1. Organized five day  FDP on  "Machine Learning Models for Disease Diagnosis: A Practical Approach" during Dec 20-24, 2020