Application of extreme learning machine in plant disease prediction for highly imbalanced dataset A Bhatia, A Chug, A Prakash Singh Journal of Statistics and Management Systems 23 (6), 1059-1068, 2020 | 69 | 2020 |
A novel framework for image-based plant disease detection using hybrid deep learning approach A Chug, A Bhatia, AP Singh, D Singh Soft Computing 27, 13613–13638, 2023 | 56 | 2023 |
Hybrid SVM-LR Classifier for Powdery Mildew Disease Prediction in Tomato Plant A Bhatia, A Chug, AP Singh 7th International Conference on Signal Processing and Integrated Networks …, 2020 | 47 | 2020 |
Recent Advancements in Multimedia Big Data Computing for IoT Applications in Precision Agriculture: Opportunities, Issues, and Challenges S Verma, A Bhatia, A Chug, AP Singh Multimedia Big Data Computing for IoT Applications 163, 391-416, 2019 | 47 | 2019 |
Statistical analysis of machine learning techniques for predicting powdery mildew disease in tomato plants A Bhatia, A Chug, AP Singh International Journal of Intelligent Engineering Informatics 9 (1), 24-58, 2021 | 19 | 2021 |
Plant Disease Detection for High Dimensional Imbalanced Dataset using an Enhanced Decision Tree Approach A Bhatia, A Chug, AP Singh International Journal of Future Generation Communication and Networking 13 …, 2020 | 18 | 2020 |
A machine learning-based spray prediction model for tomato powdery mildew disease A Bhatia, A Chug, AP Singh, RP Singh, D Singh Indian Phytopathology, 1-6, 2022 | 11 | 2022 |
A Forecasting Technique for Powdery Mildew Disease Prediction in Tomato Plants A Bhatia, A Chug, AP Singh, RP Singh, D Singh Proceedings of Second Doctoral Symposium on Computational Intelligence …, 2022 | 8 | 2022 |
Fractional mega trend diffusion function-based feature extraction for plant disease prediction A Bhatia, A Chug, AP Singh, D Singh International Journal of Machine Learning and Cybernetics 14 (1), 187-212, 2023 | 5 | 2023 |
A hybrid approach for noise reduction-based optimal classifier using genetic algorithm: A case study in plant disease prediction A Bhatia, A Chug, AP Singh, D Singh Intelligent Data Analysis 26 (4), 1023-1049, 2022 | 3 | 2022 |
Investigate the Impact of Resampling Techniques on Imbalanced Datasets: A Case Study in Plant Disease Prediction A Bhatia, A Chug, AP Singh, D Singh 2021 Thirteenth International Conference on Contemporary Computing (IC3-2021 …, 2021 | 3 | 2021 |
Advance shadow edge detection and removal (ASEDR) A Bhatia, J Yadav, E Jain International Journal of Computational Intelligence Research 13 (2), 253-259, 2017 | 2 | 2017 |
Internet of Things (IOT): Confronts and Applications J Yadav, A Bhatia, Sangeeta, E Jain, N Goyal International Journal for Research in Applied Science & Engineering …, 2017 | 1 | 2017 |
Bank Loan Approval Repayment Prediction System Using Machine Learning Models M Ball, V Mehta, A Bhatia, N Malik, K Jindal Advancement of Intelligent Computational Methods and Technologies, 61-65, 2024 | | 2024 |
Improving Knowledge Representation Using Knowledge Graphs: Tools and Techniques A Malik, N Malik, A Bhatia International Conference on Intelligent Computing for Sustainable …, 2023 | | 2023 |
Air-Quality Index Prediction Using Auto Ml Library, TPOT R Saxena, K Jindal, N Malik, A Bhatia 2023 14th International Conference on Computing Communication and Networking …, 2023 | | 2023 |
A Deep Learning-Based Forecasting System to Predict Early Blight Disease in Tomato Plants A Bhatia, A Chug, AP Singh, D Singh Management of Postharvest Diseases and Value Addition of Horticultural Crops …, 2022 | | 2022 |
A Multi-Sensor and Image-Based Fusion Framework for Automated Detection of Early Blight Disease in Tomato Plants AP Singh, A Chug, A Bhatia IN Patent App. 202,111,047,712, 2021 | | 2021 |
MFPMT: A Machine Learning-Based Forecasting System for Powdery Mildew Disease in Tomato Plant A Bhatia, A Chug, AP Singh 7th International Conference on Phytopathology in Achieving UN Sustainable …, 2020 | | 2020 |
Spray Prediction Models for Powdery Mildew Disease in Tomato A Bhatia, A Chug, AP Singh 8th Asian-Australasian Conference on Precision Agriculture (8ACPA-2019), 278, 2019 | | 2019 |