531 citations · 577 across the 6 of their papers we have counts for
6 papers
Advancements in Weed Mapping: A Systematic Review
Mohammad Jahanbakht, Alex Olsen, Ross Marchant +2
Weed mapping plays a critical role in precision management by providing accurate and timely data on weed distribution, enabling targeted control and reduced herbicide use. This min…
Semi-Supervised Weed Detection for Rapid Deployment and Enhanced Efficiency
Alzayat Saleh, Alex Olsen, Jake Wood +2
Weeds present a significant challenge in agriculture, causing yield loss and requiring expensive control measures. Automatic weed detection using computer vision and deep learning…
FieldNet: Efficient Real-Time Shadow Removal for Enhanced Vision in Field Robotics
Alzayat Saleh, Alex Olsen, Jake Wood +2
Shadows significantly hinder computer vision tasks in outdoor environments, particularly in field robotics, where varying lighting conditions complicate object detection and locali…
Precision Robotic Spot-Spraying: Reducing Herbicide Use and Enhancing Environmental Outcomes in Sugarcane
Mostafa Rahimi Azghadi, Alex Olsen, Jake Wood +5
Precise robotic weed control plays an essential role in precision agriculture. It can help significantly reduce the environmental impact of herbicides while reducing weed managemen…
WeedCLR: Weed Contrastive Learning through Visual Representations with Class-Optimized Loss in Long-Tailed Datasets
Alzayat Saleh, Alex Olsen, Jake Wood +2
Image classification is a crucial task in modern weed management and crop intervention technologies. However, the limited size, diversity, and balance of existing weed datasets hin…
DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning
Alex Olsen, Dmitry A. Konovalov, Bronson Philippa +10
Robotic weed control has seen increased research of late with its potential for boosting productivity in agriculture. Majority of works focus on developing robotics for croplands,…