1 citations · 1 across the 4 of their papers we have counts for
5 papers
RoLID-11K: A Dashcam Dataset for Small-Object Roadside Litter Detection
Tao Wu, Qing Xu, Xiangjian He +3
Roadside litter poses environmental, safety and economic challenges, yet current monitoring relies on labour-intensive surveys and public reporting, providing limited spatial cover…
Getting the Numbers Right$\unicode{x2014}$Modelling Multi-Class Object Counting in Dense and Varied Scenes
Villanelle O'Reilly, Jonathan Cox, Georgios Leontidis +3
Density map estimation enables accurate object counting in heavily occluded, and densely packed scenes where detection-based counting fails. In multi-class density estimation, clas…
Habitat Classification from Ground-Level Imagery Using Deep Neural Networks
Hongrui Shi, Lisa Norton, Lucy Ridding +6
Habitat assessment at local scales -- critical for enhancing biodiversity and guiding conservation priorities -- often relies on expert field surveys that can be costly, motivating…
Unsupervised Tomato Split Anomaly Detection using Hyperspectral Imaging and Variational Autoencoders
Mahmoud Abdulsalam, Usman Zahidi, Bradley Hurst +3
Tomato anomalies/damages pose a significant challenge in greenhouse farming. While this method of cultivation benefits from efficient resource utilization, anomalies can significan…
DeepVerge: Classification of Roadside Verge Biodiversity and Conservation Potential
Andrew Perrett, Charlie Barnes, Mark Schofield +3
Open space grassland is being increasingly farmed or built upon, leading to a ramping up of conservation efforts targeting roadside verges. Approximately half of all UK grassland s…