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Lightweight Vision Transformer Compression for On-Device Plant Disease Detection in Resource-Constrained Agricultural Field Conditions

Paper recorded by Signals 4 on 2026-09-04 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-04 on arXiv · recorded by Signals 4 on 2026-09-07

Category: cs.AI · 人工智能 · first seen 2026-09-07

Abstract

Chilli (Capsicum annuum) is one of India's most economically significant crops, yet its productivity is persistently threatened by diseases that are difficult to identify without expert intervention. While Vision Transformers (ViTs) have achieved high classification accuracy, their large computational footprint makes deployment on resource constrained devices challenging. Existing compression appr

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#175 most recent of 300 cs.AI papers we have recorded · ↑ newer: The History Is the Detector: Executing CVE Patch History, End-to-End · ↓ older: Technical Manual for a Toolkit for Measuring Contextual Individuation
Cite this page: Lightweight Vision Transformer Compression for On-Device Plant Disease Detection in Resource-Constrained Agricultural Field Conditions: the #175 most recent of 300 cs.AI papers we have recorded (as of 2026-09-04). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/lightweight-vision-transformer-compression-for-on-device-plant-disease-detection.html
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