On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network

On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network

<p>This research work aims to develop a deep learning-based crop classification framework for remotely sensed time series data. Tobacco is a major revenue generating crop of Khyber Pakhtunkhwa (KP) province of Pakistan, with over 90% of the country’s Tobacco production. In order to analyze the...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Nasru Minallah (9427338) (author)
مؤلفون آخرون:	Mohsin Tariq (4266667) (author), Najam Aziz (9427341) (author), Waleed Khan (9427344) (author), Atiq ur Rehman (3044409) (author), Samir Brahim Belhaouari (9427347) (author)
منشور في:	2020
الموضوعات:	Agricultural, veterinary and food sciences Crop and pasture production Engineering Geomatic engineering Information and computing sciences Artificial intelligence Machine learning Crops Nicotiana Deep learning Artificial neural networks Machine learning algorithms Neural networks Wheat
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