Foraist

Completed Projects

List of Industrial and Academic projects completed by Foraist.

Malaria pathogen detection on thick blood smear images.

– An application to detect malaria pathogen in microscopic images of thick blood smears using Intel NCS2 and OpenVINO.

Coral Trout – Quality Score Task (autonomous optical grading).

– A desktop application to capture images of live coral fish via Wi-Fi controlled camera and upload to AWS cloud for colour grading based on deep learning CNN.

Defect classification for fruit sorter machine.

– Deep learning CNN based classification of defect categories for macadamia nuts sorting machine in commercial setting.

Polygon pipeline.

– A desktop application to automatically process raw videos (fruits/flowers) and GPS captured using farm utility vehicle to generate per row-side trimmed videos of orchard blocks for processing with deep learning object detectors.

Mango harvester.

– Machine vision desktop application displaying multiple depth cameras and GUI controls for up to 16 picking arms loaded with deep learning model for fruit detection.

Fruit-sizing app.

– A mobile/desktop application for sampling on-tree mango fruit sizes from images using computer vision algorithm to inform size distribution and yield estimation at orchard level.

Fruit detection and counting.

– A desktop application for on-tree mango fruit detection and counting using deep learning CNN and object tracking to inform yield for commercial orchards.

Flower detection and classification.

– A desktop application for on-tree mango flower panicle detection and developmental stage classification using deep learning CNN to inform peak flowering event and spatial variability for commercial orchards.

Fruit yield estimation.

– Deep learning CNN, MLP and hybrid methods for accurate fruit yield estimation using fruit count, fruit occlusion and tree canopy architecture.

Tree trunk detection.

A desktop application for tree trunk using deep learning CNN to localize individual trees for yield association in commercial orchards