activity
20202025
most citedKiwifruit detection in challenging conditions

6 citations · 19 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2025

Pallet Detection And Localisation From Synthetic Data

Henri Mueller, Yechan Kim, Trevor Gee +1

The global warehousing industry is experiencing rapid growth, with the market size projected to grow at an annual rate of 8.1% from 2024 to 2030 [Grand View Research, 2021]. This e…

cs.CV2024★ 2 cited

Detection of Spider Mites on Labrador Beans through Machine Learning Approaches Using Custom Datasets

Violet Liu, Jason Chen, Ans Qureshi +1

Amidst growing food production demands, early plant disease detection is essential to safeguard crops; this study proposes a visual machine learning approach for plant disease dete…

cs.RO2024★ 1 cited

Improving Pallet Detection Using Synthetic Data

Henry Gann, Josiah Bull, Trevor Gee +1

The use of synthetic data in machine learning saves a significant amount of time when implementing an effective object detector. However, there is limited research in this domain.…

cs.RO2024★ 3 cited

Does ChatGPT and Whisper Make Humanoid Robots More Relatable?

Xiaohui Chen, Katherine Luo, Trevor Gee +1

Humanoid robots are designed to be relatable to humans for applications such as customer support and helpdesk services. However, many such systems, including Softbank's Pepper, fal…

cs.RO2023

Seeing the Fruit for the Leaves: Robotically Mapping Apple Fruitlets in a Commercial Orchard

Ans Qureshi, David Smith, Trevor Gee +12

Aotearoa New Zealand has a strong and growing apple industry but struggles to access workers to complete skilled, seasonal tasks such as thinning. To ensure effective thinning and…

cs.CV2023

Visual based Tomato Size Measurement System for an Indoor Farming Environment

Andy Kweon, Vishnu Hu, Jong Yoon Lim +7

As technology progresses, smart automated systems will serve an increasingly important role in the agricultural industry. Current existing vision systems for yield estimation face…

cs.CV2023

Look how they have grown: Non-destructive Leaf Detection and Size Estimation of Tomato Plants for 3D Growth Monitoring

Yuning Xing, Dexter Pham, Henry Williams +5

Smart farming is a growing field as technology advances. Plant characteristics are crucial indicators for monitoring plant growth. Research has been done to estimate characteristic…

cs.CV2023★ 2 cited

Pallet Detection from Synthetic Data Using Game Engines

Jouveer Naidoo, Nicholas Bates, Trevor Gee +1

This research sets out to assess the viability of using game engines to generate synthetic training data for machine learning in the context of pallet segmentation. Using synthetic…

cs.RO2023★ 1 cited

Seeing the Fruit for the Leaves: Towards Automated Apple Fruitlet Thinning

Ans Qureshi, Neville Loh, Young Min Kwon +10

Following a global trend, the lack of reliable access to skilled labour is causing critical issues for the effective management of apple orchards. One of the primary challenges is…

cs.CV2020★ 6 cited

Kiwifruit detection in challenging conditions

Mahla Nejati, Nicky Penhall, Henry Williams +4

Accurate and reliable kiwifruit detection is one of the biggest challenges in developing a selective fruit harvesting robot. The vision system of an orchard robot faces difficultie…

cs.RO2020★ 1 cited

Design of a sensing module for a kiwifruit flower pollinator robot

Mahla Nejati, Ho Seok Ahn, Bruce MacDonald

This paper describes steps taken to develop a sensing module for a robotic kiwifruit flower pollinator, which could be integrated into an imaging module and a spray module. The pap…

cs.CV2020★ 3 cited

Deep Neural Network Based Real-time Kiwi Fruit Flower Detection in an Orchard Environment

JongYoon Lim, Ho Seok Ahn, Mahla Nejati +3

In this paper, we present a novel approach to kiwi fruit flower detection using Deep Neural Networks (DNNs) to build an accurate, fast, and robust autonomous pollination robot syst…