| Computational prediction of disease detection and insect identification using xception model L Cleetus, A Raji Sukumar, N Hemalatha bioRxiv, 2021.08. 10.455608, 2021 | 9 | 2021 |
| Genome-wide analysis and identification of genes related to expansin gene family in indica rice N Hemalatha, MK Rajesh, NK Narayanan International Journal of Bioinformatics Research and Applications 7 (2), 162-167, 2011 | 7 | 2011 |
| Classification of fruits and vegetables using machine and deep learning approach N Hemalatha, P Sukhetha, R Sukumar 2022 International Conference on Trends in Quantum Computing and Emerging …, 2022 | 6 | 2022 |
| Classification of fruits and vegetables using ResNet model. P Sukhetha, N Hemalatha, R Sukumar agriRxiv, 20210317450, 2021 | 5 | 2021 |
| Text based smart answering system in agriculture using rnn R Sukumar, N Hemalatha, S Sarin, RM CA Proceedings of the 18th International Conference on Natural Language …, 2021 | 4 | 2021 |
| Structural basis for recognition of Gibberellin by its receptor GID1 (GA-INSENSITIVE DWARF1) in Oil Palm S Rahman, A Vasu, KP Gangaraj, N Hemalatha, MK Rajesh Int. J. Innov. Res. Comput. Commun. Eng 3, 257-262, 2015 | 4 | 2015 |
| Machine learning algorithm for predicting ethylene responsive transcription factor in rice using an ensemble classifier N Hemalatha, VF Brendon, MM Shihab, MK Rajesh Procedia Computer Science 49, 128-135, 2015 | 4 | 2015 |
| Computational model of coconut maturity detection using YOLO and Roboflow PP Narasimha, KC Nayak, CP Ajmal, N Hemalatha Redshine Archive 2, 2023 | 3 | 2023 |
| Genome-wide analysis of putative ERF and DREB gene families in Indica Rice (O. sativa L. subsp. Indica) N Hemalatha, MK Rajesh, NK Narayanan | 3 | 2012 |
| Applications of deep learning in agriculture (pest-detection) N Golatkar, N Hemalatha Redshine Arch 1, 2023 | 2 | 2023 |
| Text based smart answering system in agriculture using RNN. CA Rose Mary, A Raji Sukumar, N Hemalatha agriRxiv, 20210310498, 2021 | 2 | 2021 |
| A machine learning approach for detecting MAP kinase in the genome of Oryza sativa L. ssp. indica NKN Hemalatha, N., M. K. Rajesh IEEE Conference on Computational Intelligence in Bioinformatics and …, 2014 | 2 | 2014 |
| 5 ONCOGENOMIC ANALYSIS TO FIND THE ROLE OF BRCA1 AND BRCA2 IN MALE SM Andrian, A Benny, N Hemalatha INFORMATION TECHNOLOGY & BIOINFORMATICS INTERNATIONAL CONFERENCE ON ADVANCE …, 2024 | 1 | 2024 |
| Computational yield prediction of Rice using KNN regression N Hemalatha, W Akhil, R Vinod Computer Vision and Robotics: Proceedings of CVR 2022, 295-308, 2023 | 1 | 2023 |
| Decision tree classification of digital soil, weather, crop mapping and yield prediction using linear regression with region influences. A Rini, N Hemalatha, R Sukumar Agrirxiv, 20210310499, 2021 | 1 | 2021 |
| Computational prediction model for pepper yield prediction using support vector regression. A Wilson, N Hemalatha, R Sukumar agriRxiv, 20210310468, 2021 | 1 | 2021 |
| Machine learning model for rice yield prediction using KNN regression. A Wilson, R Sukumar, N Hemalatha agriRxiv, 20210310469, 2021 | 1 | 2021 |
| Prediction of Plastic Degrading Microbes N Hemalatha, A Wilson, T Akhil bioRxiv, 2021.08. 01.454681, 2021 | 1 | 2021 |
| PRGPred: A platform for prediction of domains of resistance gene analogue (RGA) in Arecaceae developed by using machine learning algorithms MKR Mathodiyil S. Manjula, Kaitheri E. Rachana , Sudalaimuthu. Naganeeswaran ... J. BioSci. Biotechnol. 4 (3), 327-338, 2015 | 1 | 2015 |
| Computational prediction of the secretome of Ganoderma lucidum CU Rahul, M Babu, N Hemalatha, MK Rajesh Int J Innovative Res Computer Commun Eng 3 (7), 275-280, 2015 | 1 | 2015 |
Rajesh M. K.CENTRAL PLANTATION CROPS RESEARCH INSTITUTE, KASARAGOD, KERALA 671124, INDIAVerified email at icar.gov.in
