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CNN and transfer learning methods with augmentation for citrus leaf diseases detection using PaaS cloud on mobile

Lanjewar, M.; Parab, J.S. (Springer, 2024)
Portable system to detect starch adulteration in turmeric using NIR spectroscopy

Lanjewar, M.; Morajkar, P.P.; Parab, J.S. (Elsevier, 2024)
Machine learning based technique to predict the water adulterant in milk using portable near infrared spectroscopy

Lanjewar, M.; Parab, J.S.; Kamat, R.K. (Elsevier, 2024)
Python Programming Recipes for IoT Applications

Parab, J.S.; Lanjewar, M.; Sequeira, M.; Naik, G.M.; Shaikh, A.Y. (Springer, 2023)
FoG and Cloud Computing with Jetson Nano (Chapter 5)

Parab, J.S.; Lanjewar, M.; Sequeira, M.; Naik, G.M.; Shaikh, A.Y. (Springer, 2023)
MicroPython PyBoard for IoT (Chapter 4)

Parab, J.S. (Springer, 2023)
Simple Applications with Raspberry Pi (Chapter 3)

Parab, J.S. (Springer, 2023)
Hybrid method for accurate starch estimation in adulterated turmeric using Vis-NIR spectroscopy

Lanjewar, M.; Morajkar, P.P.; Parab, J.S. (Taylor & Francis, 2023)
Efficient deep learning model for de-husked Areca nut classification

Patil, S.; Naik, A.; Parab, J.S. (Applied and Natural Science Foundation, 2023)
Improving hemoglobin estimation accuracy through standardizing of light-emitting diode power

Pinto, C.F.; Parab, J.S.; Sequeira, M.; Naik, G.M. (Institute of Advanced Engineering and Science (IAES), 2022)

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