MSc project: Agricultural production accounts for major revenue source for both developed and developing economies. There is a financial cost that the farmer has to bear dealing with unwanted plants like weeds. Weeds compete for the soil nutrients, sunlight, water and space with the agricultural crops. Weeds detection in agricultural crops has significant challenges such as accurately determining the position of the weed in natural conditions remains a difficult task because of the high variability in weed size, color, occlusion, high density of weed and crop plants and the overlapping of plant parts. In this concern, the project aims to detect weed in a sugar beet crop dataset using Vision Transformers (ViT).