Traditional grain quality testing process involved manually counting and segregating grains based on their physical appearance, making the process time-consuming.

Designed and implemented DNASegment, a segmentation model based on the Vision Transformer architecture capable of counting the total number of grains in an image and classifying them based on their physical appearance.

Made the grain quality testing process 2.5x faster than the traditional manual method.