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Found 7 papers, 1 papers with code
Seed Kernel Counting using Domain Randomization and Object Tracking Neural Networks
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.
Fractional Vegetation Cover Estimation using Hough Lines and Linear Iterative Clustering
This paper presents a new image processing algorithm to determine the amount of vegetation cover present in a given area, called fractional vegetation cover.
Seed Classification using Synthetic Image Datasets Generated from Low-Altitude UAV Imagery
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.
PiBase: An IoT-based Security System using Raspberry Pi and Google Firebase
The app lets the user create a list of non-intruders and anyone that is not on the list is identified as an intruder.
Classification of Seeds using Domain Randomization on Self-Supervised Learning Frameworks
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.
Seed Phenotyping on Neural Networks using Domain Randomization and Transfer Learning
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.
Bombus Species Image Classification
Entomologists, ecologists and others struggle to rapidly and accurately identify the species of bumble bees they encounter in their field work and research.
