Weed Classification Using Explainable Multi-Resolution Slot Attention

Weed Classification Using Explainable Multi-Resolution Slot Attention

In agriculture, explainable deep neural networks (DNNs) can be used to pinpoint the discriminative part of weeds for an imagery classification task, albeit at a low resolution, to control the weed population. This paper proposes the use of a multi-layer attention procedure based on a transformer com...

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Bibliographic Details
Main Authors: Sadaf Farkhani, Søren Kelstrup Skovsen, Mads Dyrmann, Rasmus Nyholm Jørgensen, Henrik Karstoft
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Sensors
Subjects:
transformer
slot attention
explainable neural network
fusion rule
weed classification
weed identification key
Online Access:https://www.mdpi.com/1424-8220/21/20/6705

Internet

https://www.mdpi.com/1424-8220/21/20/6705

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