Web-SpikeSegNet: Deep Learning Framework for Recognition and Counting of Spikes From Visual Images of Wheat Plants

Web-SpikeSegNet: Deep Learning Framework for Recognition and Counting of Spikes From Visual Images of Wheat Plants

Computer vision with deep learning is emerging as a significant approach for non-invasive and non-destructive plant phenotyping. Spikes are the reproductive organs of wheat plants. Detection and counting of spikes considered the grain-bearing organ have great importance in the phenomics study of lar...

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Bibliographic Details
Main Authors: Tanuj Misra, Alka Arora, Sudeep Marwaha, Ranjeet Ranjan Jha, Mrinmoy Ray, Rajni Jain, A. R. Rao, Eldho Varghese, Shailendra Kumar, Sudhir Kumar, Aditya Nigam, Rabi Narayan Sahoo, Viswanathan Chinnusamy
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Computer vision
deep learning
deep encoder-decoder
hourglass
image analysis
spike detection and counting
Online Access:https://ieeexplore.ieee.org/document/9432817/

Internet

https://ieeexplore.ieee.org/document/9432817/

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