Back to search

Article

Lightweight Deep Learning Models for Efficient Classification of Plant-Parasitic Nematodes on Resource-Constrained Devices

2026-04-28

Abstract excerpt

<title>Abstract</title> <p>Agricultural productivity underpins global food security, yet it faces growing threats from plant diseases. Among these Plant Parasitic Nematodes (PPNs) contribute to an estimated annual crop loss exceeding \$157 billion. Existing methods for identifying PPNs are labor‑intensive and require specialized expertise, which limits their practical application in low resource settings. To addr...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
d62e9ce6-92a8-596d-9d20-f030a6512ce9
DOI
10.21203/rs.3.rs-9526310/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Lightweight Deep Learning Models for Efficient Classification of Plant-Parasitic Nematodes on Resource-Constrained DevicesDOI 10.21203/rs.3.rs-9526310/v1
Select a neighboring publication to make it the new centre.