Enabling Intelligence on the Edge: Leveraging Edge Impulse to Deploy Multiple Deep Learning Models on Edge Devices for Tomato Leaf Disease Detection

Enabling Intelligence on the Edge: Leveraging Edge Impulse to Deploy Multiple Deep Learning Models on Edge Devices for Tomato Leaf Disease Detection

Tomato diseases, including Leaf blight, Leaf curl, Septoria leaf spot, and Verticillium wilt, are responsible for up to 50% of annual yield loss, significantly impacting global tomato production, valued at approximately USD 87 billion. In Ghana, there is a yield gap of about 50% in tomato production...

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Bibliographic Details
Main Authors: Dennis Agyemanh Nana Gookyi, Fortunatus Aabangbio Wulnye, Michael Wilson, Paul Danquah, Samuel Akwasi Danso, Awudu Amadu Gariba
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:AgriEngineering
Subjects:
Edge Impulse
TensorFlow
CNN
tomato disease detection
agriculture
microcontroller unit
Online Access:https://www.mdpi.com/2624-7402/6/4/203
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