Thesis Subject: Pelvic Organ Segmentation in MRI acquisitions
SoyBeans Quality Analysis
Agricultural application of machine vision and machine learning concepts. We worked in collaboration with the Estación Experimental Agropecuaria Oliveros from the INTA institute, to research about an increasing regional agricultural problem. Due to drought and heat stress, the soybeen seeds remain immature presenting germination and industrial problems. This symptom is tightly related to the appearance of green pigmentation in the seeds. An Automatic Grading of Green Intensity in Soybean Seeds system prototype is the final result of this multidisciplinary project.
- “Soybeans maturation problems.”
- “Feature extraction and analysis.”
- “Low cost classification system. “
The system comprises from the acquisition of the image up to the classification results. Starting from a common flat-bed scanner image we segment and extract essential features in order to classify each seed using a trained state-of-art machine learning classifier. The system achieved better results than the experts in a controlled validation experiment.