David Lamb

About

Dr. David Lamb is a leading researcher at the intersection of precision agriculture, robotics, and artificial intelligence. His work focuses on developing advanced sensor technologies and machine learning algorithms to revolutionize crop health assessment and automate agricultural tasks. A key contribution is the creation of the Colour Feature Extreme Learning Machine (CF-ELM) and its variants, including the Multiple-Expert (MEC-ELM) and Segmented Colour Feature (SCF-ELM) models. These algorithms enable ultra-fast, real-time object detection in complex pastoral and agricultural landscapes, making them ideal for deployment on autonomous robots. His highly cited 2020 work on active and passive electro-optical sensors (54 citations) provides a foundational framework for non-destructive, spatialized plant disease detection. Dr. Lamb also explores the broader role of robotics, AI, and service automation in event management. With over 150 combined citations across his top papers, his innovations are directly shaping the future of smart farming, offering practical, high-speed solutions for crop monitoring and robotic intervention.

Research Focus

Key Achievements

Top Papers

1. 1
   Active and Passive Electro-Optical Sensors for Health Assessment in Food Crops

   54 citations · 2020
2. 2
   Real-time object detection in agricultural/remote environments using the multiple-expert colour feature extreme learning machine (MEC-ELM)

   45 citations · 2018
3. 3
   The Role of Robots, Artificial Intelligence, and Service Automation in Events

   27 citations · 2019
4. 4
   Fast object detection in pastoral landscapes using a Colour Feature Extreme Learning Machine

   20 citations · 2017
5. 5
   The Segmented Colour Feature Extreme Learning Machine: Applications in Agricultural Robotics

   11 citations · 2021

Key Collaborators

Contact & Links