no code implementations • 10 Aug 2023 • Venkat Margapuri, Prapti Thapaliya, Mitchell Neilsen
Furthermore, we propose a seed kernel counter that uses a low-cost mechanical hopper, trained YOLOv8 neural network model, and object tracking algorithms on StrongSORT and ByteTrack to estimate cereal yield from videos.
1 code implementation • 30 Apr 2022 • Venkat Margapuri, Trevor Rife, Chaney Courtney, Brandon Schlautman, Kai Zhao, Mitchell Neilsen
This paper presents a new image processing algorithm to determine the amount of vegetation cover present in a given area, called fractional vegetation cover.
no code implementations • 6 Oct 2021 • Venkat Margapuri, Niketa Penumajji, Mitchell Neilsen
Plant breeding programs extensively monitor the evolution of seed kernels for seed certification, wherein lies the need to appropriately label the seed kernels by type and quality.
no code implementations • 29 Jul 2021 • Venkat Margapuri, Niketa Penumajji, Mitchell Neilsen
The app lets the user create a list of non-intruders and anyone that is not on the list is identified as an intruder.
no code implementations • 29 Mar 2021 • Venkat Margapuri, Mitchell Neilsen
Generally, a plant re-searcher inspects the visual attributes of a seed such as size, shape, area, color and texture to identify the seed type, a process that is tedious and labor-intensive.
no code implementations • 24 Dec 2020 • Venkat Margapuri, Mitchell Neilsen
In order to tackle such a scenario, the idea of domain randomization i. e. the technique of applying models trained on images containing simulated objects to real-world objects, is considered.
no code implementations • 9 Jun 2020 • Venkat Margapuri, George Lavezzi, Robert Stewart, Dan Wagner
Entomologists, ecologists and others struggle to rapidly and accurately identify the species of bumble bees they encounter in their field work and research.