International Journals (Only Scopus and SCI indexed)

1. Sunil, C.K., Jaidhar, C.D., Patil, N. Cardamom Plant Disease Detection Approach Using EfficientNetV2, (2022) IEEE Access, 10, pp. 789-804. DOI: 10.1109/ACCESS.2021.3138920
2. Jayasimha, A., Mudambi, R., Pavan, P., Lokaksha, B.M., Bankapur, S., Patil, N. An effective feature extraction with deep neural network architecture for protein-secondary-structure prediction, (2021) Network Modeling Analysis in Health Informatics and Bioinformatics, Springer, 10 (1), art. no. 58, DOI: 10.1007/s13721-021-00340-4
3. Bankapur, S., Patil, N. Enhanced protein structural class prediction using effective feature modeling and ensemble of classifiers, (2021) IEEE/ACM Transactions on Computational Biology and Bioinformatics, 18 (6), pp. 2409-2419. DOI: 10.1109/TCBB.2020.2979430
4. Bankapur, S., Patil, N., An Enhanced Protein Fold Recognition for Low Similarity Datasets Using Convolutional and Skip-Gram Features with Deep Neural Network, (2021) IEEE Transactions on Nanobioscience, 20 (1), art. no. 9187655, pp. 42-49. DOI: 10.1109/TNB.2020.3022456
5. Vanahalli, M.K., Patil, N., Distributed load balancing frequent colossal closed itemset mining algorithm for high dimensional dataset, (2020) Journal of Parallel and Distributed Computing, Elsevier, 144, pp. 136-152. , DOI: 10.1016/j.jpdc.2020.05.017
6. Bankapur, S., Patil, N., ProgSIO-MSA: Progressive-based single iterative optimization framework for multiple sequence alignment using an effective scoring system, (2020) Journal of Bioinformatics and Computational Biology, 18 (2), art. no. 2050005, . DOI: 10.1142/S0219720020500055
7. Bankapur, S., Patil, N, An Effective Multi-Label Protein Sub-Chloroplast Localization Prediction by Skipped-grams of Evolutionary Profiles using Deep Neural Network, (2020) IEEE/ACM Transactions on Computational Biology and Bioinformatics, . DOI: 10.1109/TCBB.2020.3037465
8. Vanahalli, M.K., Patil, N., An efficient colossal closed itemset mining algorithm for a dataset with high dimensionality, (2020) Journal of King Saud University - Computer and Information Sciences, Eksevier. DOI: 10.1016/j.jksuci.2020.04.008
9. Kaur, K., Patil, N., A fast and novel approach based on grouping and weighted mRMR for feature selection and classification of protein sequence data, (2020) International Journal of Data Mining and Bioinformatics, Inderscience, 23 (1), pp. 47-61. DOI: 10.1504/IJDMB.2020.105435
10. Kumar, P., Bankapur, S., Patil, N., An enhanced protein secondary structure prediction using deep learning framework on hybrid profile based features, (2020) Applied Soft Computing Journal, Elsevier, 86, art. no. 105926,  DOI: 10.1016/j.asoc.2019.105926
11. Vanahalli, M.K., Patil, N., An efficient dynamic switching algorithm for mining colossal closed itemsets from high dimensional datasets, (2019) Data and Knowledge Engineering, Elsevier, 123, art. no. 101721, DOI: 10.1016/j.datak.2019.101721
12. Vanahalli, M.K., Patil, N. An efficient parallel row enumerated algorithm for mining frequent colossal closed itemsets from high dimensional datasets, (2019) Information Sciences, Elsevier, 496, pp. 343-362., DOI: 10.1016/j.ins.2018.08.009
13. Gangavarapu, T., Patil, N., A novel filter–wrapper hybrid greedy ensemble approach optimized using the genetic algorithm to reduce the dimensionality of high-dimensional biomedical datasets, (2019) Applied Soft Computing Journal, Elsevier, 81, art. no. 105538, DOI: 10.1016/j.asoc.2019.105538
14. Narasimhan, M., Balasubramanian, B., Kumar, S.D., Patil, N., EGA-FMC: Enhanced genetic algorithm-based fuzzy k-modes clustering for categorical data, (2018),  International Journal of Bio-Inspired Computation, Inderscience, 11 (4), pp. 219-228. DOI: 10.1504/IJBIC.2018.092801

Conference Publications (Only Scopus indexed, 2020 onwards)

1. Pavan, R., Nara, M., Gopinath, S., Patil, N., Bayesian optimization and gradient boosting to detect phishing websites, 2021 55th Annual Conference on Information Sciences and Systems, CISS 2021, art. no. 9400317, DOI: 10.1109/CISS50987.2021.9400317
2. Praveen, K., Patil, N., Srikanth, C.S., Vikas, J., M-CAD: Towards Multi-Categorical Auto Diagnosis of Varied Diseases using Deep Learning, (2021) Proceedings - 2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science, IRI 2021, pp. 223-227. DOI: 10.1109/IRI51335.2021.00036
3. Saini, G., Patil, N., CNN-GRU: Transforming image into sentence using GRU and attention mechanism, (2021) 12th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2021, 2021-August, pp. 487-493.
4. Sunil, C.K., Jaidhar, C.D., Patil, N, Empirical Study on Multi Convolutional Layer-based Convolutional Neural Network Classifier for Plant Leaf Disease Detection, 2020 IEEE 15th International Conference on Industrial and Information Systems, ICIIS 2020 - Proceedings, art. no. 9342729, pp. 460-465. DOI: 10.1109/ICIIS51140.2020.9342729
5. Devi, T.G., Patil, N., Analysis &evaluation of Image filtering Noise reduction technique for Microscopic Images, 2020 International Conference on Innovative Trends in Information Technology, ICITIIT 2020, art. no. 9071556, DOI: 10.1109/ICITIIT49094.2020.9071556
6. Vanahalli, M.K., Patil, N., Distributed mining of significant frequent colossal closed itemsets from long biological dataset, (2020) Advances in Intelligent Systems and Computing, 940, pp. 891-902. DOI: 10.1007/978-3-030-16657-1_83
7. Pasupulety, U., Adwaith, C.D., Hegde, S., Patil, N., Feature selection using fast ensemble learning for network intrusion detection, (2020) Advances in Intelligent Systems and Computing, 940, pp. 967-977. DOI: 10.1007/978-3-030-16657-1_90
8. Bankapur, S., Patil, N., Protein secondary structural class prediction using effective feature modeling and machine learning techniques, - 2018 IEEE 18th International Conference on Bioinformatics and Bioengineering, BIBE 2018, art. no. 8567451, pp. 18-21. DOI: 10.1109/BIBE.2018.00012