Wen‐Hao Su

About

Wen-Hao Su is a pioneering researcher at the intersection of precision agriculture, computer vision, and artificial intelligence, with a focused expertise in automated weed detection, crop recognition, and smart farming systems. His work addresses one of agriculture's most pressing challenges: developing intelligent, sustainable alternatives to labor-intensive and chemically harmful weed management practices. Su's most influential contributions center on applying deep learning architectures—particularly optimized YOLO-based models—to real-time weed-crop discrimination in field settings. His 2024 review on deep learning-based weed-crop recognition (77 citations) has become a key reference in the field, while his SE-YOLOv5x model (54 citations) demonstrated how transfer learning and visual attention mechanisms can dramatically improve detection accuracy in lettuce cultivation. Beyond detection, Su has pioneered crop signaling systems that enable non-invasive plant identification for precision care, as evidenced by his early foundational work published in 2019–2020. His 2025 comprehensive review on multimodal fusion for sustainable plant care (41 citations) signals his expanding vision toward Agriculture 4.0 frameworks. Collectively accumulating over 370 citations, Su's body of work is shaping the future of robotic weeding, intelligent agricultural equipment, and environmentally responsible crop management.

Research Focus

Key Achievements

Top Papers

1. 1
   Deep Learning-Based Weed–Crop Recognition for Smart Agricultural Equipment: A Review

   77 citations · 2024
2. 2
   SE-YOLOv5x: An Optimized Model Based on Transfer Learning and Visual Attention Mechanism for Identifying and Localizing Weeds and Vegetables

   54 citations · 2022
3. 3
   Real-time lettuce-weed localization and weed severity classification based on lightweight YOLO convolutional neural networks for intelligent intra-row weed control

   46 citations · 2024
4. 4
   Deep Learning in Multimodal Fusion for Sustainable Plant Care: A Comprehensive Review

   41 citations · 2025
5. 5
   Automatic Lettuce Weed Detection and Classification Based on Optimized Convolutional Neural Networks for Robotic Weed Control

   36 citations · 2024
6. 6
   Crop plant signaling for real-time plant identification in smart farm: A systematic review and new concept in artificial intelligence for automated weed control

   32 citations · 2020
7. 7
   Development of a systemic crop signalling system for automated real-time plant care in vegetable crops

   27 citations · 2020
8. 8
   Non-destructive evaluation of photostability of crop signaling compounds and dose effects on celery vigor for precision plant identification using computer vision

   26 citations · 2019
9. 9
   A SPH-YOLOv5x-Based Automatic System for Intra-Row Weed Control in Lettuce

   21 citations · 2023
10. 10
    An Intelligent Robot Based on Optimized YOLOv11l for Weed Control in Lettuce

    13 citations · 2025

Key Collaborators

Contact & Links