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Dr. Anshul Bhatia
Dr. Anshul Bhatia
Assistant Professor, USAR, GGSIP University EDC
在 ipu.ac.in 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
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
692020
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
562023
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
472020
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
472019
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
192021
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
182020
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
112022
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
82022
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
52023
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
32022
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
32021
Advance shadow edge detection and removal (ASEDR)
A Bhatia, J Yadav, E Jain
International Journal of Computational Intelligence Research 13 (2), 253-259, 2017
22017
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
12017
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
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