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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Bibliographic Details
Main Author: Nasru Minallah (9427338) (author)
Other Authors: Mohsin Tariq (4266667) (author), Najam Aziz (9427341) (author), Waleed Khan (9427344) (author), Atiq ur Rehman (3044409) (author), Samir Brahim Belhaouari (9427347) (author)
Published: 2020
Subjects:
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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